DS isn't better than Sol and Gemini in the benchmarks, but after working with them all for a while now I'm beginning to understand why people find DS _feels_ so much better.
First, it's the tok/s and TTFT from providers. Deepseek blazes through work - at quite good quality - and you don't find yourself waiting for your agents to finish.
Second is the openness. Being able to see the CoT and not being randomly blocked for cyber review. You're never wondering if it's stuck or if it will randomly fail. Combined with the great cost value.. My next subscription will probably be Z.ai
Philip-J-Fry 10 hours ago [-]
Feels better to me in the sense that it doesn't try to be too clever. When I ask it to do things it actually generates code that a developer would write. That still lets me build software in layers like I do mentally. And it keeps you in control of where abstractions are.
Some people would say that you don't need this at all with the frontier llms. But when extending existing software or writing software that fits into an existing ecosystem, I find I still need to offer a lot of guidance. And it's better that the context window isn't flooded with code that was reverted after I looked at it.
jamesbfb 10 hours ago [-]
> Some people would say that you don't need this at all with the frontier LLMs
Hit the nail on the head. Development methodologies pivoting at the whim of frontier models have been one of the things that have been worrying me as of late.
trueno 9 hours ago [-]
it doesn't worry me too much tbh. This is really just cutting corners and going this route leaves you with some kind of additive ship of theseus piece of software you don't understand and require your frontier model to work with, which just... becomes more additive and gross.
right now we're in some proverbial heyday of everyone seeing how absolutely grand of a thing they can make with frontier models.
over time i expect some old design philosophies to take hold with people who use LLM's successfully and find a place again paired with developers who understand why such layered methodologies are important... because this whole AI thing wasn't the silver bullet CEO's and crazy execs thought it was. They will eventually get sick of the support burden of badly designed stuff. i anticipate a bit of pendulum swinging back towards "still using AI, but we need smart people to do it because it's expensive and we want it done right". Right now a lot of companies are being extremely reckless imo and they haven't fully realized/felt the cost implications of trainwreck software yet.
huijzer 36 minutes ago [-]
> haven't fully realized/felt the cost implications of trainwreck software yet
As long as the API is private or not dependent on by automated systems and you have good test coverage, you can get away with bad code IMO since you can always refactor. If it looks stupid but it works (and can be refactored/fixed/improved later if needed) it aint stupid.
swader999 5 minutes ago [-]
Used to say this about dev written code, if it has tests, I can usually live with it.
LPisGood 7 hours ago [-]
What if those “cost implications” are just asking Opus 6.7 to fix whatever issue cropped up?
fn-mote 4 hours ago [-]
Exactly.
In a way, that’s the situation today. You can pay an experienced developer $$$$ to do it right, or you can outsource it and pay $$ but pay extra for more layers of review, have lots of unfixed bugs and more tech debt.
You are proposing that instead we pay the frontier model to clean it up. If it can, I expect it to cost somewhere in the neighborhood of an experienced dev because that’s the alternative. That’s the way the frontier AI companies will extracting the value of the work from you.
anukin 9 minutes ago [-]
Opus on enterprise pricing is not exactly cheap.
hazard 2 hours ago [-]
> I expect it to cost somewhere in the neighborhood of an experienced dev because that’s the alternative
But there's two ways this could be true: Frontier models costs rise, or (more likely) experience dev costs fall
TuringTest 6 hours ago [-]
In complex systems, issues keep piling up faster than you can fix them.
agile-gift0262 5 hours ago [-]
IMO the fundamental principles and "conflicts" are still the same, but many have forgotten about them with all the hype and sense of speed. The industry will slowly rediscover them.
swat535 4 hours ago [-]
Support burden? When did companies care about customer support or system maintenance?
They already did the bare minimum allocation to both despite engineering screaming at them.
I highly doubt executives are going to accept slower release and sale cycles in order to provide better support.
If anything, I expect this trend to accelerate. I’m imagining the opposite, a plethora of AI slop with increasingly burned-out engineers.
fn-mote 4 hours ago [-]
> slower release and sale cycles
Sales are out of their control.
If there’s a market for quality and you don’t have it, sales are going down no matter what the PHB wants.
If there’s not, watch out for the vibe-coded competitor.
ekidd 4 hours ago [-]
Buggy slop products will burn buyers and then people will buy less. The very-early-80s video game companies shoveled out slop, including a few games that wouldn't even launch. Which led to the Great Video Game Crash of 1983.
Abishek_Muthian 6 hours ago [-]
I've been using layered development techniques like the parent says even with frontier models, just one agent at a time with Zed.
10 hours ago [-]
brookst 7 hours ago [-]
I just use a suite of tests to enforce the mechanical standards (dry, encapsulation, etc) and arch documents for shape + reviews of new work against the two. I’m not seeing any significant drift.
ygjb 7 hours ago [-]
Yea, this is one thing that gets me. Vibe coding and freestyle prompting gets wildly different results. Starting from a set of specs and expectations routinely gets me reviewable and we'll tested code. Sure, running the full test suite alot slows things down and uses more tokens, but when I hit a five hour or weekly window, I just roll up my sleeves and start working without the model because the code is layed out the way I expected and is designed to fit my meatbag workflow and pace.
foltik 5 hours ago [-]
You must not be looking very closely yourself then.
mapontosevenths 4 hours ago [-]
When is the last time you used a frontier model? Any chance you work someplace that forces you to use last year's model (or any American open weight model)?
rjzzleep 4 hours ago [-]
> Feels better to me in the sense that it doesn't try to be too clever. When I ask it to do things it actually generates code that a developer would write. That still lets me build software in layers like I do mentally. And it keeps you in control of where abstractions are.
yes!So it's not just me. In terms of how intelligent they want to be OpenAI is at the top, then Claude. And actually when I was playing with Sol it meant that many tasks it would just try to do something else because it thought I don't know what I want. Even trying to nudge it back in the right direction wouldn't work.
I guess the models just have the cultures of their creatures.
crossroadsguy 9 hours ago [-]
> it doesn't try to be too clever
DS is miles better than GLM in this regard. I wanted to add that as PC is planning to go to GLM next.
drob518 8 hours ago [-]
Interesting. I’ve been using GLM 5.3 Flash for a couple months and found it to be great. What has it been doing that you found to be “too clever”? It sometimes gets stuck in loops. I once asked it to do a code review of a simple pattern and it went off on a 45 odyssey trying to analyze too much. But other than those, it’s been a pretty good daily workhorse. And you can’t beat the price. Even Deepseek 4.1 Flash is more expensive. And I switched to GLM 5.3 Flash from DS 4 Flash, my previous daily driver, which I also found quite good. Anyway, my point isn’t to start a “which model is better” subthread, but was just curious what behavior you’ve seen where it’s “too clever.”
crossroadsguy 3 hours ago [-]
It wastes my time. A lot! In different ways. That's the tl;dr. Really.
Keeps repeating things I settled as accepted or rejected. But what really gets on my nerves? The language it uses – that aweful, useless typical LLM languages! No AGENTS.md instruction, no per session instruction, no just two-prompts-prior instruction seems to work, hell sometimes instruction regarding that in same prompt doesn't work. GOOD/BAD example along with instruction don't work. That wastes time and zones you out! Not to mention the fatigue of to and fro. DS has been working much better. Hell Gemini 3.1 Pro works so much better than GLM. I don't have extended experience with OpenAI and Anthromic models but the free claide.ai works quite well and better than GLM 5.3 (not even flash). Albeit I must say I rarely use claude.ai for coding, but technical tasks? All the time!
GLM's best response: "No excuse. My fault. You exactly asked me not to do exactly that and so did the AGENTS.md. I failed". Love it. Except that if I press I will get that response every 5 prompts.
welovetacos 2 hours ago [-]
In my experience GLM and Claude models behave in ways that steadily drift from your directives and speak in similarly mannered "Claudese", leading me to believe that glm was more or less trained to mimic Claude. I think this reflects a very strong gravitational pull anchored at the system prompt level to specific voice and behavior directives directives. I find other models like DS and Gemini are more compliant and drift much less from my custom behavior and voice directives.
runtime_terror 6 hours ago [-]
Anecdotal but I was doing regular adversarial reviews of new work using about 5 models (mostly the open Chinese ones like DS, GLM, Qwen, Kimi, etc) and GLM routinely took much longer for similar results and the same instructions.
It would just loop on things and go down rabbit holes more. DS flash has been so consistently good I've kinda settled on it for 90% of my work.
I still use adversarial review for bigger changes where I want to make sure any issues are caught early, but I genuinely feel as tho if no new models ever get made I'd be fine with just using DS forever.
alfiedotwtf 3 hours ago [-]
What quant were you using? I’ve been using Q4_K_S for a while now and it’s been rock solid, but having tried Q3_XS, that would loop like crazy. Maybe try a bigger quantity size?
f311a 6 hours ago [-]
For me GLM thinks too much for no reason. It takes a 2-3 turns for DS where for GLM it takes up to 10.
I like giving precise instructions,”update function xx to support input yy, add tests”. There is no reason for 10 turns and 5 minutes of waiting.
zenoprax 5 hours ago [-]
I briefly tried GLM 5.3 Flash and the first thing I noticed was how slow it was followed quickly by its single-mindedness. With DS 4.1 Flash I find that it understands that not all the detail in my prompt is important. Sometimes I like to give a quick example of what I'm looking for and it can take the hint whereas GLM will seemingly reshape its worldview around this tiny detail.
DS just handles ambiguity and my bursts of detail with much more grace. I'm only using "max effort" and the CoT is reasonable compared to GLM.
dtech 2 hours ago [-]
> the first thing I noticed was how slow it
This really depends on the provider, it's a very fast model with ours
dpacmittal 3 hours ago [-]
What harness are you using?
UncleOxidant 6 hours ago [-]
> My next subscription will probably be Z.ai
Wait... you just spent 3 paragraphs singing the praises of DS... and then you say you're going to subscribe to the one that makes GLM. ?
(I do tend to agree with you, though I tend to favor GLM-5.3-flash over DS 4.1 flash.)
Matl 3 hours ago [-]
Z.ai does offer access to DS AFAIK, so I guess that's what they mean? Maybe the feeling is that it provides more value that DS's own platform since you also get GLM, not sure.
nfw2 6 hours ago [-]
maybe the point was become of the openness, they will be using z.ai?
jeremyjh 5 hours ago [-]
But it’s not at all as described in terms of work style - it’s much more like Claude.
nfw2 4 hours ago [-]
Reading quickly, I thought the open CoT was the most important piece of comment, probably just bc that seems like it would be the most useful to me.
debugging reasoning traces more effectively seems useful to find prompt issues writing custom harnesses even if it runs on stronger model later
igetspam 8 hours ago [-]
Agreed.
It doesn’t have to be better, it just had to be nearly equivalent. I’ve been doing a lot of vulnerability work lately (trying to get ahead of the bots finding exploits in our code) and the frontier models feel like a chaperone at a church dance: get too close and they show up with the ruler and enforce the safety margin. Using deepseek and glm and qwen, I’ve gotten nearly equivalent results without the constraints. I still use frontier models for things but outside of a company environment, I’m happy to spend 1/10 the money, get the same results, and not have try and trick the AI into working.
abc42 10 hours ago [-]
No need to use a chinese provider, in case that's an issue for you. https://fireworks.ai provides this model for an ok price.
dannyw 8 hours ago [-]
I'd rather my data go to China and directly to labs that release open weight models (DeepSeek is MIT licensed still); instead of closed labs and the NSA/CIA; who has far better ability to hurt me than China does.
Without getting too much into politics; over the past several decades, one country is going around starting wars, regime changes and other interventionism, or initiating economic warfare (Huawei sanctions because they were getting too competitive to US companies; GPU restrictions; tariffs; etc), and that's not one administration: it's US policy over the past few decades.
This number reports, basically, how good it is to live inside a country, while the comment that you are replying to is entirely a list of foreign policy complaints (regime changes, etc).
It's kinda like meeting someone on the street who's protesting about animal cruelty in slaughterhouses, slyly handing them a chart showing them the nutrition facts of beef, and then walking off without another word as though you've settled your case.
Like, I get the point you're trying to make, but I hope you're aware it's a non-sequitur in context?
albedoa 60 minutes ago [-]
> Like, I get the point you're trying to make, but I hope you're aware it's a non-sequitur in context?
Your hope should have been that amelius was not aware that it's a non-sequitur, because that is correctable. But then they kept posting and removed all doubt.
ashkankiani 7 hours ago [-]
Why link to a number, which means roughly nothing, instead of the specific details on the countries you're trying to compare? I have no idea how to break down or make my own assessment of what 0.83 or 0.18 means. Does that 0.83 for the US include all of the people being shipped off without due process to El Salvador, or do they count that as part of El Salvador's Human Right Index?
People like to bring up the Uyghurs immediately, but never really have the same smoke for the US. Also, do we include the prison population in human rights? Do we include access to healthcare? What about systems perpetuating poverty like lack of access to public transportation?
To pre-emptively be clear on my stance or potential bias, I stand by no country in the world. I was born in Iran, and my parents left when I was young to the US because they believed in the American Dream. The irony being that the dominos of why they left were initiated by the US and UK. And long before Trump was elected, but certainly immediately afterwards, I decided to leave the US once I had the means. (Also because of the lack of public transit, the $100k medical bills after an accident, being punched by a homeless person, and having my possessions stolen repeatedly and the cops giving me a :shrug:). I moved to Japan, where I experienced blatant racism for the first time. I moved to Hong Kong (and tbh no real complaints so far), but I am technically subject to the freedom of speech constraints on China.
I have no allegiance to any country or specific people. My allegiance is to all living beings.
amelius 6 hours ago [-]
Sorry but you're arguing against a reputable institution here.
ashkankiani 6 hours ago [-]
I'm not arguing against a reputable institution, I'm arguing against using that reputation + their final number alone without going through the process to verify the methodology myself, which you didn't link to. You only showed the conclusion, which to all of us, should mean very little until we look into how that number was arrived at.
And I don't care if they're reputable, I will look at the methodology and make my own conclusion either way. Appeals to authority are not a substitute for critical thinking.
amelius 6 hours ago [-]
We're not talking about a few % difference here. If you want to look into it then fine, but you have to come up with some really good evidence if you think you can debunk anything here.
lejalv 4 hours ago [-]
We're talking about the country that has tried multiple times to destroy their country, look up Mossadegh for the 1950s and check out the glorious bombing of a school for 2026.
I know the US thinks only its citizens are human, so "The United States has been involved in hundreds of interventions in foreign countries throughout its history, engaging in nearly 500 military interventions between 1776 and 2026, with half of these operations occurring since 1950 and over 25% occurring in the post-Cold War period” is not probably part of the reputable storytelling
pessimizer 6 hours ago [-]
There's absolutely nothing in those numbers to argue against. They are simply providing fluffy quantitative declarations in order for people who don't even claim any particular knowledge or even understanding of the details of the metric (such as yourself) to argue from authority.
If they actually said something, it would be much less effective.
> We're not talking about a few % difference here.
How may freedom percent is it again? Do you lose 1% or 20% for failing to allow foreign ownership of utilities? How many percent do you gain for stopping Russian misinformation?
amelius 6 hours ago [-]
The metric was carefully crafted by a group of experts as means of communicating a complicated topic.
I'm not going to discuss it further if you don't have anything substantial to bring to the table.
aleqs 4 hours ago [-]
'experts' lmao. Your entire argument boils down to an appeal to authority fallacy.
amelius 1 hours ago [-]
That fallacy does not apply here as the authority is legitimate and relevant.
tessier2501 4 hours ago [-]
Yes! By all means, let us appeal to authority and use institutions' reputations to shut down any discussion, rather than thinking about what these figures actually mean, what criteria they're based on, or how well they reflect reality.
edit: wording
RobotToaster 4 hours ago [-]
An institution mostly funded by the governments it happens to rank highly, and the open society foundation that's owned by George Soros, a man who's been obsessed with overthrowing China's government since the 80s. https://www.v-dem.net/about/funders/
j_maffe 6 hours ago [-]
They're not arguing against the institution. They're arguing against the metric
.
amelius 6 hours ago [-]
Yeah but the metric was invented by that reputable organization and given the enormous difference it's not worth any discussion unless they come up with something good in which case they should probably publish about it.
aleqs 4 hours ago [-]
If you don't want to have a discussion don't post pointless metrics that you don't even understand.
lejalv 4 hours ago [-]
They are arguing for you using your brain instead of tethering it to a number.
owebmaster 3 hours ago [-]
No he's arguing against your arguments and winning.
gnaritas99 29 minutes ago [-]
[dead]
yogthos 3 hours ago [-]
oh please, the US economy literally runs on slavery
lol the US was a .60 in 1789 during slavery. this chart is useless.
amelius 6 hours ago [-]
The reason the US scores a 0.6 in 1789 comes down to how composite data is aggregated and the global baseline of the 18th century.
Yes, people have put thought into this. This is why I trust institutions and not random posters on the internet.
twohaibei 5 hours ago [-]
Is WHO a reputable institution? And was it reputable between 2019-2022?
tonytamps 5 hours ago [-]
Yes
aleqs 4 hours ago [-]
The reason that US and its allies/friendlies always score high on these kinds of ratings while their enemies/adversaries always score low is because these institutions and 'experts' are directly funded by and beholden to these countries/interests.
Just look at Russia - it's score is highest in the 90s - the most corrupt and destitute time in its modern history, also happens to be when it was deemed somewhat friendly to US and friends.
aftbit 5 hours ago [-]
The biggest problem with this is that I can't run my company's own internal benchmarks against this API, because they will be trained into the next version of the model, making them worthless.
llboston 7 hours ago [-]
Have you ever wondered why Manus founders gave up billions of dollars from Meta and “voluntarily” moved back to Beijing? One country does things out in the open, while the other operates in the shadows. The latter worries me more.
throwaway27448 7 hours ago [-]
It worries me far more what people are ok with us doing in broad daylight.
> Have you ever wondered why Manus founders gave up billions of dollars from Meta and “voluntarily” moved back to Beijing?
This country wouldn't be such a shithole if we were able to bring the wealthy to heel. I suspect most people on earth see China as the more competently governed country. Understandably, this forum tends to select for people who view private investment positively, but this is clearly insufficient by itself to produce functional societies.
Der_Einzige 6 hours ago [-]
You mean the project that literally had an anus as its mascot? Wasn’t that a joke project? Maybe the government was admonishing them for naming their company “man-anus”
torginus 5 hours ago [-]
You are not really narrowing it down
vehemenz 7 hours ago [-]
This is really a roundabout way of saying you have no plans to live, or perhaps even travel, to China.
peri-cl 9 hours ago [-]
To add to this, Fireworks (and many competitors, e.g. enumerated here[0]) offer zero-data retention inference, to anyone. DeepSeek cloud does not. It's part of their terms that anything you send them is fair game for them to train models on.
(The badges next to companies indicate their privacy terms, i.e. green/yellow/red)
leftouterjoins 7 hours ago [-]
It’s pretty clear despite what they want you to think Anthropic and OpenAI train on everyone’s data who has a subsidized plan. Only way you get ZDR is by paying API prices. Also note that it is zero retention, not zero training.
peri-cl 7 hours ago [-]
> "Also note that it is zero retention, not zero training"
The "green" badges explicitly say the opposite:
> "Private: this provider does not train on prompts and does not retain prompt data."
I.e. for the example of Fireworks, this is the precise language they use to describe ZDR:
> "More technically: prompt and generation data exist only in volatile memory for the duration of the request. If prompt caching is active, some prompt data (and associated KV caches) can be stored in volatile memory for several minutes. In either case, prompt and generation data are not logged into any persistent storage."
I figure (hope) buying from DeepSeek directly benefits them the most so they can release even more improvements and open-weight models.
Plus only one country has threatened to annex mine and it wasn't China.
eli 2 hours ago [-]
It surely does. Official DeepSeek provider logs and trains off your data.
kennywinker 8 hours ago [-]
Assuming canadian or dane, but maybe there are other places he’s threatened. There are canadian inference providers running deepseek, and definitely eu ones idk about ones based in denmark.
The economic sovereignty of any nation, but especially smaller ones like canada and denmark, is harmed by sending our money out of the country when there are options available in country.
kenmacd 7 hours ago [-]
> The economic sovereignty of any nation, but especially smaller ones like canada and denmark, is harmed by sending our money out of the country when there are options available in country.
I respectfully disagree. I subscribe to the comparative advantage economic principle, so I'm fine with international trade.
kennywinker 6 hours ago [-]
What I am saying isn’t inconsistent with comparative advantage. International trade is fine, but only when it’s not a commodity easily obtained inside your own nation. Open model inference is a commodity. There is no real lost opportunity cost from using canadian owned GPUs or chinese owned ones. In fact, as a country with abundant cheap power, and physical space, canada’s probably a better place than many to run inference. That’s what I meant by “when there are options in country”.
kenmacd 5 hours ago [-]
I hear you, but as I said, I hope that buying from Deepseek gets more Deepseek. Maybe they get the same amount (or more) from a Canadian provider, and if so I might reconsider.
The 'clean power' would factor in a well, but I haven't really looked in to it. I know China is installing a ton of renewable and has a carbon market while Canada's building a new pipeline and building Alberta data centres running on natural gas, so I'm not willing to take on faith that switching is cleaner.
kennywinker 2 hours ago [-]
Fair point. Personally i don’t see value in closed models, be they chinese or american. So, it’s pretty much against my religion to pay the model creator to provide inference. Even a situation where model makers license models to providers seems better than deepseek hosted deepseek provided models.
Also, re: power. I said canada has lots of cheap power, clean was your word.
WhrRTheBaboons 41 minutes ago [-]
RE: clean power - China is by far the biggest leader in getting renewables off the ground, but they are also still comfortably the biggest polluter, so it's difficult to compare.
The unfortunate truth behind at least the solar PV boom in China is that it's driven in large part by the exploitation of Uyghurs in the Xinjiang region. One of the reasons they can sustain the pace they're going at is because while nowadays PV modules exports increasingly gravitate towards offshore fabs (Vietnam, Malaysia), domestically all the biggest PV players make full use of modern slavery within Xinjiang's re-education camps.
>International trade is fine, but only when it’s not a commodity easily obtained inside your own nation
It might be a minor nitpick, but that part is just not how the macroeconomic principle works. Abundance of a good/service within a country is irrelevant to the concept of a comparative advantage - this is counter-intuitive but but that was David Ricardo's entire point. It's not about whether production is more efficient domestically, it's whether comparative allocation of resources between multiple countries is more efficient by specialization within the different goods.
Even if you can produce "good 1" cheaper in Country A vs Country B, if Country A can instead produce "good 2" that Country B cannot, it's better for Country A to produce "good 2" domestically and import "good 1".
Now, I still agree with the original notion. It's unnecessarily risky to use services from "democratically-challenged" nations (especially imperialist ones), when safer options are available. But there's no need to twist macro 101 concepts to justify that view. Modern trade policy takes more into account than basic market efficiency.
irrkfjjffj 6 hours ago [-]
[flagged]
subscribed 6 hours ago [-]
China has annexed (or it claims so) several countries already, so it sounds like you're only concerned with yourself - probably not what you wanted to achieve.
(But I'd concede that in the field of genocide China doesn't come up as bad)
6 hours ago [-]
specproc 10 hours ago [-]
If one is not American, why prefer American? Chinese fine by me, I trust the US providers just as little.
pimeys 9 hours ago [-]
There's also European providers for these models. More than one!
I feel like I’m getting good value out of my subscription and they have the cheapest GLM-5.3 API rates I could find in Europe. I moved to them recently from Mistral for the better prices.
They do have a slightly different daily inference capacity allowance, but it’s actually not too bad once used to it. I was forced to up my game and figure out what GLM-5.3 Flash and Deepseek-4.1 Flash could actually do for me, rather than just throwing everything at GLM-5.3. Quite happily chugging along with a nice balance across them now.
I am hoping Melious make the new DS 4.1 Flash 1017 available soonest.
They do not yet. They are testing it but they go with GLM right now.
esperent 6 hours ago [-]
Which ones? And how is the price?
abc42 4 hours ago [-]
I support people making choices with full knowledge of what they are doing and what the consequences are, as much as it is possible. What I oppose is making choices without such knowledge.
pimeys 10 hours ago [-]
There are multiple others in EU, and in US. Cheaper, more expensive, slower, faster. So much choice.
itsalwaysgood 9 hours ago [-]
Completely unrelated, but it's so odd to see upside down '8's in the first column of the base tables on their pricing page.
ilaksh 7 hours ago [-]
The link points to OpenRouter with multiple providers.
> they frequently generate CoT explanations rationalizing those answers
I can't tell if this is a really human thing to do, or if it's just a sycophantic thing to do when your master likes a good story.
tclancy 7 hours ago [-]
Fair, but you can see the logprobs, right? That alone is pretty valuable.
simianwords 7 hours ago [-]
This is like one of those folk theories that have some truth but in practice it is useless.
I love COT and gives me a good idea about the thought process. Sure it doesn’t work always
alfiedotwtf 3 hours ago [-]
Same. And the biggest benefit is that you get to see if it’s heading in the wrong detection
embedding-shape 6 hours ago [-]
In practice, it does help to immediately be able to tell if you missed something or wrote something incorrect in your prompt, compared to if you didn't have access to the CoT. If you see that it goes off wondering about stuff or thinking about stuff that you know are already solved/known, you cancel the execution, edit the prompt and redo, then observe the CoT again, until you've resolved any "misdirections".
Both OpenAI and Anthropic hides so much of that, that you don't really know if it misunderstood something or you got something wrong, until all the turns are complete or you directly see tool calls that implicitly tells you something is wrong.
You don't need to read any papers to see this effect concretely when developing together with LLMs.
wetpaws 7 hours ago [-]
[dead]
xyzzy_apps 1 hours ago [-]
Absolutely!
DeepSeek feels like an excellent sparring partner.
The others feel like mind readers.
I don't have to worry about any complex context engineering / multi agent stuff if I am using DeepSeek because the sequential stuff is fast enough. I don't have to bother about touching a million context length because its cheap enough.
Where it seems to lag behind is 3d, computer use, motion graphics, design but the initial demos seem like the vision model has improved substantially.
please don't subject yourself to this. z.ai subscriptions are not a good value. just pay API rates, or use a subscription like opencode go.
MaxMatti 5 hours ago [-]
I've used the zai subscription, opencode go und cline-pass in the last few months and would recommend the latter. Zai quickly drains your quota as soon as the context window is at more than 10-20% and opencode was a bit unreliable at times.
equasar 2 hours ago [-]
Google's Argon model via antigravity is unusable, for a small code review I asked, already spent like 10% of the weekly usage, in less than 10 mins. Very useless imho.
I always find DS or Qwen to be very spot on on audit changes or plans for just a few cents.
petu 10 hours ago [-]
Is that a dig on DeepSeek not offering subscription plans?
If so OpenCode Go looks good and includes DeepSeek models (yet to try myself).
eckelhesten 9 hours ago [-]
I wonder what quantization opencode uses for DS models.
petu 6 hours ago [-]
From "What about data and privacy?" in FAQ it sounds like they don't host models themselves. e.g. it says:
DeepSeek: ZDR agreement is renewed monthly. The current agreement is valid through October 31, 2026.
https://opencode.ai/go
They also follow official DeepSeek API peak/off peak hour pricing and link to their docs:
DeepSeek V4.1 Flash / V4 Pro: Peak hours are 01:00-04:00 and 06:00-10:00 UTC, Monday through Friday; all other hours, including weekends, are Off-Peak. Learn more.
https://opencode.ai/v2/docs/console/go/#usage-limits
I think they just pass through requests to DeepSeek, so whatever upstream offers.
neya 5 hours ago [-]
I second this, I love DS and am not looking back. For Elixir, not a lot of models are good, but DS just blazes through it.
34679 4 hours ago [-]
I'm enjoying Alibaba's Token Plan. They don't have any hourly/daily cutoffs. You get your allotment for the month and use it when you want.
tyrabound 7 hours ago [-]
If I were part of a cabal that is interested in preserving control and trying to secure trillions of dollars, it would be a minor effort to nudge and bend the curve against competitors like the Asian AI complex.
jfengel 6 hours ago [-]
How would you go about that?
killingtime74 2 hours ago [-]
I think opencode go is the better value to get access to DeepSeek.
npn 8 hours ago [-]
I do not use DS for coding, but for various natural language processing tasks (even translation) in large volume, and it works wonder.
It is very capable for a lot of tasks, not only coding like the other open models.
serf 3 hours ago [-]
I like it because it does the thing I want it to do rather than moralizing.
No, I don't care about license provenance for all the components of a 30 line script that i'm using in my house, for myself to sync up some folders. No, i'm not going to find and archive the licenses for all the previous projects leading to this for future legal disclosure.
Yes, I own the DVD for the movie i'm transcoding. No I don't want to talk about the legality of rebroadcast.
Deepseek (and most chinese models as a whole) don't care . oAI and Anthropic models want to make it point #1.
... which is extra hilarious knowing the laws broken to create the damn models in the first place.
there's a literal meme about this floating around the harness/AI chats for the past few months[0]
I don't see this kind of behavior myself, I wonder if it's me not pushing the boundaries enough or me explicitly or implicitly framing the prompt in a way that makes it less likely for the agent to intervene.
crossroadsguy 9 hours ago [-]
> not being randomly blocked for cyber review
Just to test, will GLM – hosted by an infra provider other than Z.AI – also stop answering if I asked controversial questions from the pov of its country of origin? Or third party infra providers can perform some unhinging on the model before hosting? Or actually the blocking happens even before the question reaches the LLMs in that country?
(Note: my paid LLM access at this point are only via DS and GLM subs - 90-95% usage; and a free Gemini Pro access. I hope that adds some cred that I am not trying to take potshots at the their country of origin).
flexagoon 6 hours ago [-]
Depends on the question. Most models won't tell you how to make weapons because they're trained not to, but the political stuff is usually blocked on the API level
SSLy 7 hours ago [-]
to add to the corrent sibling answer, the unhinging is called abliteration by the wider community but it's hard to find someone who will serve that over API.
OsrsNeedsf2P 8 hours ago [-]
It will not. Ask DeepSeek about Tiananmen Square. It will happily answer
charcircuit 4 hours ago [-]
GLM refuses to write exploits. It's not open season with anything you want.
MangoCoffee 10 hours ago [-]
Deepseek and Muse are my go to for cheap. both work perfect for basic and mid tier tasks
pimeys 9 hours ago [-]
I mean... I ported some of my childhood Finnish shareware games for Linux and Rust with DeepSeek V4.1 Flash. It took about six hours of spelunking and finally I was pretty happy with the results! I did it twice. Tokens for both of the games were around 3 euros.
nextaccountic 10 hours ago [-]
What about mimo v2.6 pro?
FacelessJim 9 hours ago [-]
I’ve jumped between mimo and ds quite a bit lately. Mimo seems to be slightly better in terms of what it can achieve in terms of end results. But it gets there very slowly, and in a super convoluted way. Sometimes it’s almost frustrating to read its reasoning. Also I’ve noticed that it tends to not use tools in the harness as much as other models.
I usually default to ds, and if it gets stuck try mimo but usually just for fire and forget tasks. After a bit I come back and see what it did.
esafak 7 hours ago [-]
Usually great but it infuriates me sometimes with what it does. DeepSeek is more consistent and certainly faster.
esafak 7 hours ago [-]
Muse is fantastic for open source work. At least 1.3 was, for its price. Wonder makes less economic sense.
scotty79 55 minutes ago [-]
> Being able to see the CoT and not being randomly blocked for cyber review.
I had a bad experience with MiMo from Xiaomi. I had it trigger unsafe content blocks while fixing visual bugs in a completely vanilla space game it just wrote from scratch in the same session. It also got triggered for changes in some other benign greenfield app.
lmf4lol 3 hours ago [-]
and really , for 90% of standard agentic work, deepseek flash is more than good enough.
its the main driver for our Personal Assistant offering and users love it.
blahgeek 9 hours ago [-]
> Deepseek... My next subscription will probably be Z.ai
Wait wut? You do realize that they are two different companies, right?
throwa356262 8 hours ago [-]
Z.ai (well technically alibaba) used to support both GLM and DS models in their API and coding plans.
zxilly 6 hours ago [-]
z.ai was not alibaba. z.ai got glm and alibaba got qwen
jrmg 6 hours ago [-]
For us neophytes, what does this mean: “randomly blocked for cyber review”?
jakozaur 6 hours ago [-]
E.g., your prompt for simple auth works (e.g., decode JWT), but your sessions stop because you are flagged for cybersecurity risk.
The Fable is the worst offender, and it is not purely Anthropic's fault.
esperent 6 hours ago [-]
It's happened to me exactly twice in about 6 months of using codex (via pi). Both times were completely bogus and annoying but still, it's not too bad.
dannyw 6 hours ago [-]
OpenAI's models have a lot less false positives for me. Almost always smooth doing vuln scans and fixing them.
Anthropic, whether Opus 5.5 or Fable, frequently will review for security, and the classifiers fire mid-way while it's fixing something. Authentication and credential related code, including implementation, also trigger safeguards.
Earlier today, I hit what appears to be a sticky "reasoning_extraction" block when attempting to reproduce a LLM paper at small scale, and I asked it ~"tell me more about the idea [X] you considered but dropped". I'm not sure how it works or how long it lasts, but Opus 5.5 has refused to do technical LLM work for me now, even in completely new sessions.
quinndupont 8 hours ago [-]
Agreed, but don’t subscribe to z.ai; their inference is terrible. Stick with openrouter
onesandofgrain 4 hours ago [-]
Isnt Z.ai for GLM? Does Z.ai provide Deepseek?
sunaookami 10 hours ago [-]
Huh, doesn't DeepSeek take the longest because it overthinks way too much? Haven't tested this release yet but was very disappointed with past ones because it takes an eternity to do anything because it constantly overthinks and questions itself way too much instead of just starting.
pimeys 10 hours ago [-]
It thinks a bit more, but if the cache reads are free or almost free, and it blasts through 10x faster than GPT Sol/Terra/Luna, it doesn't really matter. Just don't use the max thinking for implementation, go with high or low.
jambutters 10 hours ago [-]
Why not use max thinking for implementation? For cost reasons?
pimeys 9 hours ago [-]
Because it doesn't make difference for my use. High is good enough! If you do an assistant for yourself, low is more than enough.
It reduces the speed and tends to overthink sometimes which is really annoying. For programming, 4.1/high is the bread and butter in my daily work.
AspireOne 9 hours ago [-]
For time reasons.
k__ 10 hours ago [-]
I think, as long as you don't set thinking to max and use a fitting system prompt, it's not a big issue.
davedx 9 hours ago [-]
Yes, and this version explicitly addresses that
Leynos 9 hours ago [-]
4.1 Flash on medium is a solid builder agent
sehw 9 hours ago [-]
LLMs don't think.
effortprogramme 9 hours ago [-]
I love using glm 5.3 more than deepseek because of performance
epolanski 7 hours ago [-]
For 99% of the tasks any model really would do, even GPT 5.4 from an year ago.
It's only for long running/very difficult cases that the differences are here, and they are small.
chrsw 4 hours ago [-]
I can think of plenty of tasks that even the closed frontier models fail miserably at. From my perspective we have a long way to go for these models to get better.
epolanski 4 hours ago [-]
I'm sure they exist, but it's not the bulk of the work.
chrsw 4 hours ago [-]
My prediction is that in in a few years, maybe more, the current models will be seen as so primitive that they're not worth mentioning outside of a historical context.
epolanski 2 hours ago [-]
What a bold prediction /s
Oxodao 10 hours ago [-]
also it's cheap, using it in opencode is great
abc42 10 hours ago [-]
Note that opencode routes deepseek requests to China.
Flere-Imsaho 10 hours ago [-]
I have to ask what's everyone's issue with the requests to China. We've had 25 years of American big tech basically capture all our data, and use that to make insane profits.
vehemenz 7 hours ago [-]
This is a false equivalency. American providers don't answer to their government.
jeremyjh 5 hours ago [-]
When the White House told Anthropic to take Fable offline - they did it. They are all going to comply with FISA warrants that the public will never see.
regexorcist 5 hours ago [-]
What? The US govt has in practice unlimited access to whatever that's hosted in the US, or even outside by a US company. It's called the CLOUD act.
rolymath 4 hours ago [-]
Of course they do. See Zuckerberg's episode on Joe Rogan.
speed_spread 3 hours ago [-]
Oh but they absolutely do. The difference was mainly that up to a few years ago, the American government (generally) didn't care to repress those with the "wrong" opinions. Whereas China was always quite adamant about it.
allarm 5 hours ago [-]
And that changes things how exactly? The problem is that American companies have been stealing our data for decades, not their ties to the government.
9 hours ago [-]
abc42 9 hours ago [-]
Sure. Can you tell me why that means that it's ok for Chinese big tech to capture all our data?
Turskarama 9 hours ago [-]
The government that is most likely to use your data against you is the government of the country you live in. If a foreign government wanted to use your data against you the easiest way for them to do it would ironically be to send it to your government.
Barbing 7 hours ago [-]
Makes sense in short term & for personal queries. A German or Norwegian model provider shouldn’t tattle on US Southerners seeking reproductive care.
Long-term & software engineering fronts: I hear occasional railing against “US hegemony”. Anyone concerned that if a new tech gives rise to a different country, they’ll become the source of ire instead? (This isn’t my field, at all.)
Oxodao 9 hours ago [-]
My code is opensource, china already has it. For my professional work we have entreprise plans with OpenAI / Anthropic
miroljub 9 hours ago [-]
For an average European, why is it better than routing requests to the USA?
BOOSTERHIDROGEN 9 hours ago [-]
Chime-in for an average non us citizen why is it better ?
swiftcoder 7 hours ago [-]
The argument has never been that it would be better (a domestic EU provider would obviously be better than either from a data handling perspective). But its not obviously worse
abc42 9 hours ago [-]
Valid question. I have no 100% factual answers and neither does anyone else here.
So I go with feeling, and that feeling says that China is worse. The feeling is partially supported by the fact that China is softly backing Russia in its attack against the west.
Trump's USA is obviously completely horrible, but he is also in large part a product of Russian influence, which again is part of the larger block in which China resides.
tancop 9 hours ago [-]
"The west" is a stupid idea America uses to force themselves and Israel into the same league as EU countries.
And China is not really supporting Russia, they make money off the war and want to keep it going as long as possible so both Russia and Ukraine become weak and more open to their influence. Is it evil? Absolutely, but you can't compare them to USA when Trump is actively doing regime change operations, deporting its own citizens and putting sanctions on the ICC.
Chinese communists want to stay in power at all costs but America wants to expand its power into the whole world. It's not the same level of danger at all.
akho 8 hours ago [-]
> want to keep it going as long as possible
note that the volume of EU and US support to Ukraine is obviously calibrated to the same goal.
jubilee33 8 hours ago [-]
Yes I unfortunately trust those who are motivated by money more than ideology. Greed, while horrible and ugly, is at least very predictable.
Messianic, or even utopian or pretty much any ideology, can lead to absolutely insane levels of destruction. You just don't know what true believers of any sort are willing to do.
To be fair, east and west are in relation to England, not the US.
Trump’s a smelly orange shit but the US at least pretends to have data privacy protections and we can’t legally compel companies to have back doors… yet. I think. It’s very hard to keep up with all the nonsense these days.
swiftcoder 6 hours ago [-]
> and we can’t legally compel companies to have back doors
In a post-Snowden world where the existence of PRISM is no longer a secret, I'm not sure how folks can keep stating this with a straight face
igetspam 8 hours ago [-]
If you pay for a business plan on openrouter (I know, it’s not opencode, just another option), you can geo lock providers if China is a concern.
hgoel 8 hours ago [-]
Opencode also has a setting to not route to China, though this would probably just disable the models that do not have providiers in alternative locations.
altcognito 10 hours ago [-]
Doesn’t that depend on the router service provider?
_s_a_m_ 10 hours ago [-]
still a myracle to me what people achieve with it? I tried so many things with it, everything is broken it produces
jmward01 5 hours ago [-]
This model is why OpenAI and Anthropic want regulatory hurdles. We need more diversity like this, not less. A diverse ecosystem is the only long term solution to complex problems that I know of and the challenges that the AI world is presenting is no different.
guantanamo_bob 3 hours ago [-]
Their strategy is regulatory capture.
mmaunder 3 hours ago [-]
Through fear. Specifically making the American public so scared of AI that they hand over regulatory keys to the only “experts” that can keep them safe. This is a centuries old political strategy used by some of the worst regimes including apartheid South Africa where I grew up. It’s horrifically effective.
pyronite 2 hours ago [-]
I disagree that they’ve invented some “strategy” for this.
1. They, and many other experts, have been saying the same thing since well before the current paradigm existed.
2. There is nothing about regulation that is required to give them an advantage; it’s a fallacy to suggest “regulation = advantage”
3. It would be preferable to argue the facts (is it or is it not dangerous? Why or why not?) than conspire as to why they’re stating what they and plenty of others have been saying for decades
equake 1 hours ago [-]
DeepSeek is simply amazing.
aleqs 4 hours ago [-]
100%
4 hours ago [-]
seaucre 2 hours ago [-]
I keep seeing this assertion. What regulations have they proposed that would have prevented this new model? I thought they want to pace the frontier, which this model is not.
kennywinker 2 hours ago [-]
You are taking their words literally, rather than looking at the side effects of any effort to "pace the frontier".
0xbadcafebee 22 minutes ago [-]
Dario has not (and will not) say he wants to ban Chinese models outright. But:
Do the math: 1 + 2 + 3 = he wants to regulate/ban the Chinese open weights.
Of course, Anthropic and OpenAI will then write posts about how their own models are dangerous - but that's okay, they're the good guys.
zmmmmm 32 minutes ago [-]
Go read Dario's screed on GLM, or his other one one on how your toaster could be part of a distributed open model that self replicates. Every second blog post is some doom scare about the dire consequences of open models. Go look at the new ToU [0] which are now pages and pages of things you can't do with Anthropic models. Check how they will ban your account if you are persistently mean to Claude now.
He's completely transparently campaigning for regulation. It must be very frustrating to him that the Trump admin is completely non-responsive. He probably thought Anthropic would have the whole market stitched up and water tight by now.
Literally zero, but that never stopped a good conspiracy theory, especially when half of HN hates the big labs because of fear for their own economic future.
OpenAI and Anthropic aren’t even slightly worried about DeepSeek.
mszcz 41 minutes ago [-]
Having looked at the sentiment around DeepSeek's models around this thread as well as my own experiences with it I'm going to need a little more to back up that assertion about OpenAI and Anthropic not being at least a little bit worried about DeepSeek...
WarmWash 39 minutes ago [-]
People like open models because they are free/cheap. It's not anything deeper than that. Most people will hop in whatever van is handing out free candy.
They are showing this new version scoring significantly higher across multiple coding benchmarks, beating Sol 5.6 (6.1 is the latest) across 10/11 benchmarks.
I am going back to DeepSeek for writing code. I was trying out using Sol and liking the result, but this should close a lot of that gap. I use Opus/Sol for an implementation plan and code review also use them for grilling. DeepSeek is also running verifications.
dang 3 hours ago [-]
We'll put that link in the toptext too. Thanks!
AmazingTurtle 10 hours ago [-]
so i did some apples to bananas comparison.
i let 4 different agents review the same dirty code base (200+ files changed, c++, game engine):
- deepseek v4.1 flash via deepseek API: took 20m to find one p1 issue that was relevant and a p2 issue that was irrelevant
- glm 5.3 flash NVFP4 via TP2 DGX Sparks: took 1h 5m to find a p3 documentation issue
- gpt 5.6 sol: took 5m30s for one p1 and one p2 issue. both relevant
- gpt 6.1 sol: took 4m30s for two p1 and one p2 issue. both relevant.
Worth to mention: none of those findings overlapped.
I let deepseek v4.1 flash and gpt 6.1 sol both plan fixes for the summary of the findings. in this particular scenario: gpt 6.1 sol planned to increase a buffer size from 128 to 256 to fit the 191 elements that blew past a test scenario. it included some headroom. deepseek v4.1 flash on the other hand decided to make it exactly 191 to satisfy the test, for example.
The TPS decode on deepseek is impressive. I never had a second / feeling of being left aone and though "damn this thing is working". Despite all my efforts, it took ~4x longer in a review, found less and planned worse than GPT 6.1 Sol. Wall clock time. I don't have token counts for comparison. If I were to grade those models from 1-10 (10 = top tier GG), I'd give deepseek a solid 6.5 and 6.1 sol a 7.5-8.0 maybe.
vgalin 6 hours ago [-]
LLMs are non-deterministic, you could run the same prompt on the same code base with the same models, and have different result. I don't think only one run with each model is enough to draw conclusions.
not_a_bot_4sho 3 hours ago [-]
We have to keep remembering this for some reason.
New model comes out and someone says, "it can (or can't) draw ducks on bikes" or some esoteric thing. But it's not enough statistical power to claim anything other than a personal anecdote.
I got a flat tire in downtown today. Therefore, driving in downtown causes flat tires.
Eggpants 3 hours ago [-]
Honest question about the non-deterministic nature of llms. Every programming language provides some way to control the random seed. Is this not true in GPU programming land?
teraflop 48 minutes ago [-]
Yes, but for one thing, floating-point math is non-associative so even if you use the exact same random seed, you can get different results on different implementation kernels.
For another, the dependence on a random seed is just one example of how you can get different behavior. You could just as well get different results due to e.g. a tiny difference in prompt wording or punctuation or whitespace.
If a model passes some test on 70% of random seeds, and fails on the other 30%, then knowing the rough probability of success is much more useful than knowing one random sample of the outcome.
And empirically this kind of probabilistic success is quite common, because many LLM benchmarks report "pass@k" success rates that are much higher than the "pass@1" success rate on a single attempt.
bel8 6 hours ago [-]
you probably tried with DS on max and I don't blame you.
But try it on high instead of max if possible. max is known for being overly verbose to the point of being detrimental compared to high at times.
For example Simmons svg pelican took 11 minutes on max and 1 minute on high. And they are comparable.
mosselman 7 hours ago [-]
In your case, is it a public repository that the llms might have found the issues for online?
I too am thinking about creating some benchmarks that I can understand myself. The LLM 'cheating' by finding known issues through some sort of history or online source is a path you want to protect against. Then again, you DO want them to be able to look online for people having similar issues.
qup 4 hours ago [-]
How do you get dirty changes into a public repo online?
verdverm 7 hours ago [-]
> Worth to mention: none of those findings overlapped.
This is why using multiple model families is important. Don't limit yourself by being a stan for this or that company.
dannyw 6 hours ago [-]
Especially when $10-$20 on OpenRouter with e.g. DeepSeek (or any other inference provider, or their official API) will get you very, very far.
runtime_terror 11 minutes ago [-]
Gets me about a day or two lol
david-gpu 6 hours ago [-]
That may be the case, but simply running the same code review twice with the same model may give very different results as well. Impossible to know with the information we have.
hartator 6 hours ago [-]
> Worth to mention: none of those findings overlapped.
Yet to be obsolete.
vatsachak 6 hours ago [-]
If none of the findings overlapped then LLMs are either
- For some reason choosing only a subset of issues.
- Different LLMs actually learn different things.
I suspect the former since they do this for me and it's extremely annoying sometimes
qup 4 hours ago [-]
3 - non deterministic, lazy
ProphetOfParado 9 hours ago [-]
What is p1, p2?
This read like a conversation you were having in your head -- unfiltered.
taylorfinley 2 hours ago [-]
Very commonly used acronyms in business/SWE contexts.
The lower the number the higher the priority, e.g. if production is broken someone might say "This is p -1" (higher than your highest priority).
P0 is "do this immediately", P1 is very important, P2/P3 are like "nice to haves." P100 would mean something like "we will never do this"
snqb 9 hours ago [-]
priority 1,2 etc, more like severity of the cases
icantevenhold 8 hours ago [-]
It’s a very common abbreviation; i had no issue understanding GPs post tbh
jdthedisciple 8 hours ago [-]
Was that the old DS 4.1 Flash or 4.1 Flash 1017?
AmazingTurtle 8 hours ago [-]
I tried it out today, was the new one: 1017.
ilaksh 7 hours ago [-]
What reasoning effort?
esafak 7 hours ago [-]
Flagship gpt models are crazy efficient. 6.1 Sol is like a savant that looks at a problem and spits out the answer seemingly without thinking.
aleqs 6 hours ago [-]
Opposite of my experience - openai models, and codex are clearly the slowest (out of 5 different models/harnesses I use on a regular basis).
pmxi 12 hours ago [-]
Hilarious sentence: "DeepSeek-V4.1-Flash-1017 is a minor update to DeepSeek-V4.1-Flash, delivering substantial improvements across reasoning, coding, agentic tasks, and visual benchmarks." (emphasis mine)
freakynit 12 hours ago [-]
Kinda shows their team is more engineers than marketers.
boutell 10 hours ago [-]
But with that version number, it's not a "minor" update! It's a patchlevel update! -Engineer
10 hours ago [-]
stavros 10 hours ago [-]
Strictly speaking, it just shows they aren't marketers. Bad copy doesn't tell us anything about their engineering skill.
Derelicte 9 hours ago [-]
It's not a bad copy, or at least that's not what the person you responded to is insinuating.
Deepseep-v4.1-Flash-1017 is a minor update. A major update is something like Deepseek-v5-Flash.
lcnPylGDnU4H9OF 7 hours ago [-]
> It's not a bad copy, or at least that's not what the person you responded to is insinuating.
FWIW, GP didn't write "a bad copy" but "bad copy", referring to the marketing sentence quoted by OP, rather than the model that was just released (as I presume "a bad copy" sounds, maybe like it's called that because it's [again, presumably] distilled?). "Copy", especially in a marketing context, is a written message.
qup 4 hours ago [-]
Strictly speaking, it's the substantial improvements that tell us about their engineering skill.
nchmy 10 hours ago [-]
Strictly speaking, they didn't say anything about their engineering skill
barrell 7 hours ago [-]
To me this implies they continued the training run for 4.1 and it improved. A 4.2 would imply they changed something about how it’s trained/how inference works, and a 5.0 would be a major update (who knows what would have changed).
This is just my headcanon though.
jaynetics 12 hours ago [-]
It's not really contradictory, minor changes can have major effects.
mdp2021 12 hours ago [-]
So they meant a "small" update - "conservative", "inexpensive"...
An example when using a less frequent term actually reduces specificity.
NekkoDroid 2 hours ago [-]
Changing TREE(2) to TREE(3) is a small change on the input, but a... lets just call it big... change in the output.
halJordan 4 hours ago [-]
No, they used minor correctly.
nkmnz 11 hours ago [-]
That's one small step for a man, one giant leap for mankind.
cardboard9926 12 hours ago [-]
Hoping it's minor relative to what's coming
LPisGood 7 hours ago [-]
Minor updates can provide substantial improvements sometimes, it really depends on the specifics.
varispeed 7 hours ago [-]
Remember when we were dumbfounded why our service is slow despite having implemented quite robust caching mechanism. Turns out simply the flag that enables it was hardcoded to false. So it was minor update (changed flag to true), but provided substantial speed up.
ilaksh 7 hours ago [-]
They changed how it works substantially. I think it should be 4.2.
skeledrew 7 hours ago [-]
Quiet confidence backed by provenance :).
surgical_fire 11 hours ago [-]
It's a bit refreshing to read updates from an AI lab without bullshit doomerism and overwhelming sense of self-importance from shit like OpenAI and Claude.
Also, DS is an excellent model.
fivedogit 11 hours ago [-]
I'm at 1 trying to get to 10. I move to 2. Minor update. 100% improvement towards goal.
These are not mutually exclusive.
ReptileMan 12 hours ago [-]
That is how exponential functions work. Improve every aspect of a system with 1% and you may get easily 50% more performance.
vrganj 11 hours ago [-]
It's about playing to two different audiences.
The CCP requires extensive certification for new major releases, to make sure a model doesn't do anything they don't want it to.
To get around this, Chinese labs only bump versions when they have to and usually claim it's a minor update.
Then on the other side, they're obviously trying to market to the tech crowd...
epolanski 11 hours ago [-]
Source?
est 10 hours ago [-]
Everything in China is strictly regulated but loosely enforced. Just take that as a grain of salt
vrganj 11 hours ago [-]
Drum Tower podcast (from the Economist, paywalled) about Chinese AI.
Would highly recommend it, it's IMO the only serious Western reporting about China.
tw1984 9 hours ago [-]
> the only serious Western reporting about China.
as good as Gordon Chang.
vrganj 9 hours ago [-]
I don't know who that is, but from a quick Google he doesn't exactly seem trustworthy?
excannuk 8 hours ago [-]
[dead]
apejcic 9 hours ago [-]
Its a great update, I ran a benchmark comparing verbosity and intelligence compared to old weights.
- Reasoning effort = 1 is now actually usable and produces 2.5x less tokens than old weights, without intelligence lost.
- Overall 20% less tokens at each reasoning effort.
- Same intelligence and same tool-calling pattern.
Improved on exactly the items that I hear people complain about with the previous checkpoint!
ilitirit 9 hours ago [-]
I've been using DS v4.1 Flash daily for nearly a month now on Agent Swarm experiments. I've tested it against GLM-5.3-flash and Opus 5.5. DS 4.1 comes out tops for me. Opus 5.5 is still the smartest, but DS 4.1's speed and price more than make up for the "intelligence" gap. I've ran Chief/Builder/Reviewer swarms autonomously for multiple days. I think my new workflow is going to have DS 4.1 Flash do all the engineering and just have Opus review its work. 4.1 Flash really is a very impressive model. Kudos to the Deepseek team.
ilaksh 7 hours ago [-]
Ok but this is a new model with significant architectural differences and new training run.
ilitirit 6 hours ago [-]
Then I guess all that it changes is that my proposed setup gets even better?
dannyw 6 hours ago [-]
Huh? This is a new checkpoint. It has identical architecture, only different weights, and most likely just more post-training.
Much like Qwen 3.8 Next; which is qwen4-exp in a lot of the code/patches, there's usually a tick-tock cycle with LLMs. That said, it's hard to know for closed frontier models.
ilaksh 5 hours ago [-]
It's not identical, it has vision built in and asymmetric active from encode to decode.
DeepSeek delivery deliberately uses confusing version numbers.
staticman2 5 hours ago [-]
4.1 flash was already multimodal. What do you mean by "It's not identical, it has vision built in..."
ilaksh 3 hours ago [-]
Sorry I forgot that already happened with the release last month and thought it was new in this one.
weknowbetter 20 minutes ago [-]
I essentially only use DeepSeek. Almost always the flash variant. I've found that I don't really need frontier models if I'm doing most of the thinking myself and just using the agent to output code quickly.
freakynit 3 hours ago [-]
Mario one-shotted by deepseek-v4.1-flsh-1017 (in high mode, not even max) with sound and programmatically generated assets in under 5 minutes: https://mario-dsv4-1-flash-1017.pagey.site/
olavgg 11 hours ago [-]
I really like the having DeepSeek Flash + Opus 5.5 as advisor/reviewer at the moment. I run through a $200 Claude Code subscription in less than 24 hours now just for a single project, and I hate fiddling with different accounts every day. Now that I get a 200 USD api credits inlcuded with the subscriptions I have rewritten my coding agent workflow completely.
equasar 2 hours ago [-]
I'm baffled, my $20 is enough for me to do some consulting, personal projects and side work, and still cannot outran my quotas, I'm building different kind of things: flutter apps, dotnet backend, database, front end, architecture diagrams, code exploration, tests, PowerShell scripts.
How people spend more than 200 usd monthly is beyond my understanding, are you guys so inefficient with the usage? or I am the opposite?
theowaway213456 1 hours ago [-]
Without any context for what you're working on, I'd have to assume the reason you don't hit the $20 subscription limit is that you're either not using it very often, or you're working on some relatively basic CRUD app that doesn't require it to think very deeply.
I tear through my $200 subscription because I often have 3-4 agents running simultaneously, exploring performance optimizations, building features, monitoring production rollouts, or investigating production problems/customer issues in parallel.
The downside is that I do spend most of my time reading the agent's output these days.
rpastuszak 11 hours ago [-]
> I run through a $200 Claude Code subscription in less than 24 hours now just for a single project
How?
olavgg 11 hours ago [-]
Its easy when you spawn a couple of subagents in a homelab with a rack with 5+ servers.
This is how one of my claude code session looks like right now, one prompt from yesterday:
Not sure if this will help you but it helped me. I was using subagents and workflows for lots of long running tasks, and part of that work included running tests. If tests took longer than 5 minutes, the cache expired, and the whole thing was then being processed as uncached input.
I created a skill to better manage agents, including a way to keep the caches valid, and it has decreased my usage considerably. I now struggle to use my 100% each week and I hit claude hard. I have a reset expiring in 5 days and I'm trying to burn down the tokens (68% with 3d 8h left) quickly so I can use my reset before it expires.
Token efficiency just means understanding the way the system works. Best person to help with that... my old friend claude.
dotancohen 10 hours ago [-]
After I stopped letting Claude run tests, my token usage went from "gone by Wednesday" to "what can I automate this Saturday so my tokens won't go to waste".
tasuki 6 hours ago [-]
What is the reason for this? Surely running tests by itself isn't necessarily token-expensive? And it provides cheap feedback for the agent: to see whether they're breaking things.
dotancohen 6 hours ago [-]
My guess is that the LLM (usually Sonnet or Opus in my case) is burning tokens polling to see if the output finished - and there is often a lot of it. My current project is Rust, Python, and Kotlin for what it's worth.
I don't actually know the real mechanism, I came across this serendipitously.
erincandescent 3 hours ago [-]
By default Anthropic's token cache TTL is 5 minutes. If your tests take >5m to execute, when the LLM resumes your entire context is a cache miss
dotancohen 20 minutes ago [-]
Do you have a link to the docs for that? Thanks.
tasuki 2 hours ago [-]
There are many reasons why your test suite shouldn't take >5m to execute. This is just one of them.
dotancohen 19 minutes ago [-]
I've worked on projects where the test suite would take hours.
tomrod 8 hours ago [-]
How do you do that?
dotancohen 6 hours ago [-]
I just told it that I want to run the tests, because so much of the code was vibed at that point and I felt I was losing understanding of the application. A few days of that and I could see that my token use was much lower than usual. Going back to LLM-run testing returned the high token usage.
olavgg 10 hours ago [-]
Yeah, I should see if I can create a similar skill. The tests do spend some time to complete.
Claude: Confirmed: 195M of the 212M cache tokens (92%) come from full re-writes after 5+ minute gaps, accounting for 77% of relative cost. Now I'll check the existing wrappers so the skill
builds on them.
RALaBarge 9 hours ago [-]
Yesterday in my CC there was an update that added a feature to auto compact immediately prior to the cache being invalidated.
stefan_ 6 hours ago [-]
And I immediately turned it off because that just invites utter churn and stupidity. Part of that is just CC though, their compaction is miles behind Codex.
iamflimflam1 10 hours ago [-]
Some to think about with both Claude and skills.
Can you invert things. What’s deterministic and what needs “thinking”?
Can you create a script that runs things chaining together the deterministic parts with calling out to Claude for glue that needs “thinking”.
wolfy1993 10 hours ago [-]
Don't suppose you would be happy to share the skill? Or is it fairly unique to your work flow?
I think the tests problem is really having an impact for me. Hadn't considered it before so thanks for flagging.
raylad 10 hours ago [-]
How do you keep the caches valid?
entrope 10 hours ago [-]
Not OP, but I typically ask it to report status of whatever is running; it can run a background task that reports to it every N minutes. With Claude Code in VS Code and a Pro subscription, it seems like the one-hour cache is the default, making it an issue less often.
j45 10 hours ago [-]
Ask Claude, it's pretty wild to see.
nextaccountic 10 hours ago [-]
> including a way to keep the caches valid
Maybe doing bogus small requests to prevent the cache from expiring?
I mean in the API you can set the cache expiration time right? But I guess claude code can't do this
oblio 10 hours ago [-]
> my old friend claude.
Awfully new old friend.
dotancohen 10 hours ago [-]
Google is the ex, Altavista is the high school sweetheart who tragically passed at a young age.
bluerooibos 8 hours ago [-]
I have some fairly large personal software projects and I still don't understand what useful work people are getting out of burning all these tokens on unattended agents.
What exactly are they doing for you that's giving you $200 of value in such a short timeframe?
7 hours ago [-]
devtor 10 hours ago [-]
As a dev who hasn't used LLMs as an embedded part of their work, and uncertain about it all, i'd be curious to know:
- How long do you reckon it would take a human to do the task?
- What percentage of features/ feature-extensions you add would have been done at all if you didn't have agentic assistance? Is there a tension between llm productivity gains and 'because we can' feature additions?
- Are many of the tasks for throwaway v1 features, exploratory tries?
- How speced out is the work you give it, eg did this task have pages of specs, how long did the spec take to write?
- How deeply will you manually review the work and how much time will it take? Will you read all the code / review at a high level and interrogate with llm / have the llm review and self iterate?
olavgg 7 hours ago [-]
For what I am currently doing, years, if not a decade or maybe even two. Claude has already been running for 3 months constantly working on this project. I've been trying to do this several times before, but the scope outgrew my available time/life, too big for one person. But now I can actually build a production release by just setting the direction and let Claude to all the wiring, plumbing, tests etc.
I do now add all the major features I want, and write a task list where I add a few more minor tasks each week that just come to my mind. I need to write them down before I forget. I often ask Claude to implement several different implementations/algorithms and compare them. There are plenty of trade-offs, which usually end up in building configuration profiles, so the application can work optimally in multiple environments.
The specification is actually really large, and has grown over time as I've been learning and new ideas has come to my mind. I do not review/audit the code, it's massive would take me months, no chance! I do however use code inspection/audit tools like TSAN, ASAN and more. I will also spend time on full code reviews with the coming Fable 5.5 when a release is about ready. I do however review behavior together with Claude, and this is also where the specification grow, because this and that should be possible, but not this and that. User stories also helps.
devtor 3 hours ago [-]
Thanks, appreciate the reply.
lifeisloving 7 hours ago [-]
Keep doing what you're doing, this guy clearly is just revving his engine because he likes the way it sounds and can afford the gasoline. I wouldnt be asking people like this for advise, they're completely off the rails.
There's no reason to blow through tokens this way, there's a 99% chance nobody uses the output (except maybe themselves).
cloudie78 9 hours ago [-]
Yes, but what was the task that they were working on? This tells nothing.
That’s the “how” we’re wondering about.
olavgg 11 hours ago [-]
[flagged]
lifeisloving 7 hours ago [-]
You're doing this wrong.
ramigb 11 hours ago [-]
I swear I have the same question in my head always when I read such statements! I have never once reached 90% that includes everyday usage across multiple repos, artefact generation, device debugging, long running harness work!
I am not saying OP is not telling the truth. I just really want to understand!
dgacmu 9 hours ago [-]
I decided to try something a little weird research wise the other day analyzing about a thousand older research papers and burned through my $100 chatgpt sub + 3 resets in three hours and only finished half of them. It's the first time I've done that, though.
MisterMunchkin 8 hours ago [-]
It’s because they don’t know what they’re doing. It’s like when openAI was using 10,000 agent clusters to solve problems… then realised the model could do the same work on its own and solve the same problem.
Anyone who tells you they have a “team of subagents” and “code reviewer” agents and “project manager” agents doesn’t know what they are doing. That’s how they burn thousands of dollars in a day.
senordevnyc 8 hours ago [-]
Do you have a source for OpenAI discovering they can solve Navier Stokes with a single agent instead of a 10k swarm?
I think I’ll trust the experience of the people in the labs who have unlimited token budgets and are running experiments continuously over some anonymous rando slinging mud on the internet.
Also my own experience, which says having code reviewer agents is one billion percent useful. That comment alone completely disqualifies you as a reliable source of info.
pheggs 11 hours ago [-]
in my experience there's a huge difference in token usage when creating new projects versus working on existing ones
TomGarden 11 hours ago [-]
Not OP, but I used to run out in a few days, for me it was a matter of suboptimal code review practices with many subagents looking at different aspects, often expanded to look at more than the diff.
4 hours ago [-]
hugodan 11 hours ago [-]
not reviewing its ongoing work and spawning subagents that end up looping each other
fahrvrgnugen 11 hours ago [-]
Loading tons of MCPs and never compacting
imadierich 11 hours ago [-]
[dead]
nimchimpsky 11 hours ago [-]
[dead]
monster_truck 11 hours ago [-]
I can drain a $200 OAI plan in 2 hours flat working on my 10 projects simultaneously.
Maybe you're not being ambitious enough with these things? They are at their most fun when you spec out sprawling architecture documents and watch 1+8 astras buzzsaw through it.
I'm only at 260B for the year, though. I'm sure someone who has used more will be along shortly to chime in
E: The other subthread talking about tests is correct. Expensive models should not waste a single second waiting on tests or validation. If you cannot assign a single cheap model to be the test bitch, then just tell them to frontload everything and clean up later as a single wave.
ricardobayes 10 hours ago [-]
Not meant as a bad faith response but have you shipped anything? Do you have income from this? Why 10 projects apart from fueling ADHD and "never finishing a project"?
joshstrange 10 hours ago [-]
Not OP and while I’m not draining my accounts in a single day/hour, I’m hitting limits with a $200-Claude and $100-OpenAI account.
> Have you shipping anything?
Yes, hundreds of PRs and shipped new features to 3 different platforms (day job and 2 side-business apps/platforms I’ve been developing for many years, pre-LLM). Those new features have gone out to customers and been used.
> Do you have income from this?
Well my day job for one, and I’ve been able to more easily sell to new clients with my side business. Without the changes I’ve shipped I would have been able to land a couple of the clients I’ve signed on recently.
I don’t think OP’s message implied they are never finishing a project, maybe they edited it?
In addition to the 3 income-generating projects, I have a number of other “just for me” projects. Some are mature now and only need occasional development when I want a new feature. Some are in flux as I build them out (like my “software factory”).
At this point I’m limited by compute and tokens more than anything else.
ImaCake 9 hours ago [-]
Does work pay for your subscription? I think many workplaces would worry about personal accounts for work projects.
EDIT: but thanks for a useful answer to OP's question. As a programming dabbler I also find it hard to imagine how to push much past the 5hr limit on $20USD subscription.
joshstrange 8 hours ago [-]
Work provides a stipend/reimbursement of $100, the rest I pay for.
It’s paid for itself though, at least from my side business income.
tedk-42 10 hours ago [-]
Some of us want to build and don't care that it doesn't monetise.
Geof25 7 hours ago [-]
Surely such people does not have 100usd/hour budget?
loveparade 10 hours ago [-]
Would love to see these 10 projects that are being worked on simultaneously
zmmmmm 27 minutes ago [-]
> I run through a $200 Claude Code subscription in less than 24 hours now just for a single project
I would be worried about your methodology when the subscription party ends. Make no mistake, one day, the party is ending and the people who are dining out on approaches that burn massive tokens are in for a rude shock.
olejorgenb 9 hours ago [-]
After opus 5.5 release I find it very hard to run out on a 100 sub...
newsy-combi 8 hours ago [-]
I'll bite. Wtf are you working on that takes $200 a day and you're willing to pay for?
Geof25 7 hours ago [-]
By not using existing tools and one shooting everything through the API - I.e. instead of decompile via Ghidra they will try to get source via capstone genersted assembly.
It is like putting a jet engine on a shipping container and wondering why it needs to be constantly kept in afterburner to at least scrape on the road while smarter users put wheels on the shipping container.
thomasmarcelis 11 hours ago [-]
Interesting, coming from a similar situation, I'm interested what workflow you landed on. Opus planning + available to be called for deep thinking + opus reviwer? or?
aleqs 2 hours ago [-]
Yeah the Claude/anthropic usage is quite arbitrary, I also run through my entire 20x pro plan in 1-2 days. Codex has slightly better usage levels, but is annoying to use for many reasons. DeepSeek flash (direct or via opencode go) is the best value model I've found so far.
ilaksh 7 hours ago [-]
This is a new model.
sick_of_slop 6 hours ago [-]
[dead]
_R_ 11 hours ago [-]
[flagged]
cmiles8 7 hours ago [-]
Honestly given how good the open weight models are getting I don’t see a viable business model for OpenAI and Anthropic anymore. The profit is in the compute, not the model. OpenAI and Anthropic spent all their money renting compute from others so yes they can sell lightweight model inference but they have a massive structural disadvantage now as others can always sell good-enough inference much cheaper.
There’s also zero stickiness to models and most companies now have their own internal routing utilities so devs and users can just keep the same API endpoint and move between models with a single line of code swap.
Unless something changes with the big labs and fast, they look pretty f*cked.
theowaway213456 6 hours ago [-]
People will pay for more intelligent models. Astra and Fable are more intelligent than these open weight models and can solve problems that are much more difficult, and that's extremely valuable. It's not any more complicated than that.
preommr 6 hours ago [-]
> It's not any more complicated than that.
It is more complicated than that when the valuations and business plans are contingent on those companies AI having complete dominance at every level.
If companies only use frontier models for occasional difficult tasks, not only does that affect volume, it basically elminates stickiness and incentivizes companies to instead of using their products continuosly, find ways to move from the expensive stuff to the cheaper stuff.
cmiles8 6 hours ago [-]
Yes but that’s a tiny portion of AI use cases. Maybe 1-2% max. The big labs need a lot more than that to survive.
You’re assuming other model creators can’t build these mega models. Evidence is they’ve simply decided it’s a fools game to do so and they’re focused on where the use cases are.
grumple 3 hours ago [-]
Fable is behind Opus (which is also much cheaper) at this point in benchmarking.
niek_pas 6 hours ago [-]
I don’t know what I’m talking about but it seems to me OpenAI is heavily emphasizing productization of LLMs. Dots, ChatGPT Work, scheduled tasks, in-app projects etc.
Starlevel004 6 hours ago [-]
Being able to directly distill their huge frontier models into Luna/Haiku-level models puts them a step ahead still.
rikima_ 2 hours ago [-]
i hate dario's politics, but i still find claude's eco system easier to use. Design/Artifacts is very convenient for people like me who has zero UI/UX expertise, and claude code's remote session works seamlessly on ios with a well-design client interface while you have to deal with ssh and typing in cli with your iphone keyboard if you are using opencode/omp etc
desolate_muffin 6 hours ago [-]
And yet, nearly all of enterprise money spent on AI tokens in the US is going to either OpenAI or Anthropic.
cmiles8 6 hours ago [-]
That trajectory appears to be changing. Virtually every company I see is shifting more and more to open weight models. Anthropic’s slowing growth rate is already spooking investors and that shift is just getting started.
greenavocado 6 hours ago [-]
That's why they are constantly fearmongering and trying to get other models outlawed. If nothing else, under the pretense of national security.
ytxm 12 hours ago [-]
It passed my threshold for not caring to try new models back with DS4, I use it for literally everything. Announcements of new models in the series always feel curious, because it doesn't really feel like there's much left to fix that would improve on what's already there for any task I know of.
It's a bit like obsessing over patch releases of some software after a major upgrade already solved the original problem long ago.
xiphias2 12 hours ago [-]
I have quite the opposite experience: I can do any concrete coding change with any model, but the intelligence limit just doesn't go through more complex debugging examples.
And then when I try a smart model, like Astra medium and it solves it (I had a firmware bug in my new laptop where I couldn't charge through USB-C) on the first try (altough with a repo already having lots of information about the hardware/firmware/debugging programs/traces), I realize how much time I'm losing on the few examples that the less intelligent models are just not able to debug and solve.
KronisLV 11 hours ago [-]
Also they can work in completely new domains, like Astra and Opus 5.5 starting to be able to use something like Blender. Currently they still often do horrible topology and basic UV mistakes, and the animations are really bad, but who knows where they’ll be in 5 years.
oefrha 9 hours ago [-]
I don’t think these are completely new domains in training. Like I’ve taken up offers to help code up AI training material just to see what they’re up to and get a sneak peek at how the sausage is made, no idea who these front companies are working for of course, but they pay for all kinds of fringe cases and Blender wouldn’t even be considered fringe in what I saw at the beginning of the year. (I was only there to observe, never submitted anything, so I didn’t betray you guys by helping train your replacements.)
squidbeak 11 hours ago [-]
5 years? Look at the leaps since last November. Since the Spring, even.
jck 9 hours ago [-]
Very cool!
Is your laptop something like framework which has open source firmware?
I(and many other people) have a similar issue with usb-c charging not working consistently. I've been meaning to try one of these new smart models to help me debug the issue.
xiphias2 8 hours ago [-]
ASUS Zephyrus, but it was able to reverse engineer the ports and I was able to download the firware from the controller itself, write an emulator that emulates running the firmware on multiple controllers with different instruction sets (the USB Power Delivery controller is RISC-V) and the communication between them. Also it found out how to read the communication buffer that was on the devices for debugging, which helped it understand the USB data packets that were doing the handshaking and voltage/current negotiation.
I had to reboot my laptop a few times though until I got to this, but it was a fun experience anyways.
At this point open source isn't as much advantage as long as the firmware is not encrypted :)
jck 7 hours ago [-]
Wow, that is impressive. I've been meaning to do this by hand to fix the issue on my Lenovo IdeaPad for a while but haven't gotten around to it.
I'll try handing it off to one of these new frontier models.
7 hours ago [-]
11 hours ago [-]
lifeisloving 6 hours ago [-]
Yeah, but for some reason people think they need SOTA to help them work on their side/indie projects.
Like if we needed PhD intelligence for productivity tools and SaaS platforms, why weren't we hiring PhDs to build things before.
99.99% of people do not need SOTA ai.
pimeys 11 hours ago [-]
Speed and price. You should try the 4.1 Flash on one of the fast providers. It's pretty crazy how fast this model works, and it's great for iterative software development because you can steer it fast to where you want to go.
How are these high-speed providers close to matching the API rates from deepseek?
pimeys 11 hours ago [-]
Seems that V4.1 Flash is quite cheap to serve. Especially how it implements the cache, meaning the cache pricing can be very low depending on how you implement it in your inference engine.
Depends on your use case. But if you do software development with a harness such as oh-my-pi, your cache rates are probably somewhere above 98%. Coralbricks has free cache reads, meaning it's much cheaper than the Deepseek API rates.
Lithosai is more expensive especially in the ultra tier. It's if you want extremely snappy and fast responses, which is important e.g. for a personal assistant where every second counts.
If you generate a lot of output, you're better off with the Deepseek API rates.
lifeisloving 6 hours ago [-]
Ive never needed an assistant pre or post ai to reply to me in 100ms at a clip of 500 words per sec. See you in 15 min, Im making some cofeee.
arvid-lind 6 hours ago [-]
same here, but surely the trends will follow every other profit-seeking web app ever and distill down to a competition over attention.
andrepd 11 hours ago [-]
Where does one even get decent ZDR provider? I'm wary of sending sensitive data but not at a scale where I would build my own machine.
therealpygon 9 hours ago [-]
You just search around, or heck, just ask Google for inference providers that are ZDR and whatever else you want. Just make sure to read their terms/privacy and review the security center. You will have to request access if you are wanting to get into the deeper details.
Outside of major players like Amazon/Google which have compatible offerings available, I believe together.ai, fireworks.ai, and deepinfra.com are, as best as I can tell, US-based (if that matters in your situation) SOC2/HIPPA/ZDR. Each of them offer serverless model hosting with caching, which is going to be the cheapest overall. Most of them also offer private AI deployment which is more expensive but your entirely own instance. Some of them more heavily quantize their models (deepinfra) so take that into your workload considerations. I included deepinfra because they tend to have some the new models sooner than others or have models the others don’t (like mimo). IMO, together > fireworks > deepinfra.
However, you’ll have to keep in mind that for true ZDR you give up caching which increases your inference costs, so it depends on how “Zero” you need the zero to be and on what timeframe. If you just don’t want your data being trained on, normal use is fine imo. If you are working on something actually sensitive (like, because of NDA agreements and such), then they might not be the right choice and you may be looking at more expensive offerings or building a machine.
One note: you have to pay attention to the source of the inference. Many (similar to open router) offer models that are pass-throughs to a providers API, but they are pretty clearly marked. Just make sure the model is marked as serverless when evaluating new ones. This is where a proxy comes in handy so you can prevent your LLM from accessing a different models from the specific ones you’ve vetted.
ArtRichards 9 hours ago [-]
I like privatemode.ai for better than ZDR, encrypted attested hardware (in EU)
Same. I'm just happy sticking with them and am consistently impressed. Cost is so good and kind of keeps you honest.
mmoustafa 12 hours ago [-]
definitely could use less thinking time and lower token usage, which is what this bump is focused on
mdp2021 12 hours ago [-]
> improve on what's already there for any task I know of
What about "good governance"?
Does it have zero hallucinations? Does it reflect thoroughly on every single idea it uses, verifying its solidity?
a11r 5 hours ago [-]
A negative datapoint - We have been evaluated prior Deepseek Flash models (both the original 4.1 flash and the smaller 4.0 flash) and they have been overthinkers. Our workload is well defined but moderately difficult coding tasks and among open weight models GLM5.3 flash performs best with Qwen3.8 flash next a close second. DeepSeek 4.1 flash fails at lower thinking levels and spends a huge amount of tokens (an order of magnitude more) at the highest thinking levels where it is able to successfully complete the tasks. I will evaluate this newest release since they specifically claim "the model reduces task execution time and output length", but keeping my hopes low.
pornel 3 hours ago [-]
v4 was a worse overthinker. 4.1 mostly fixed that. It still prefers to plan everything before making a single file change.
If I'm impatient I switch to Luna for a single turn just to get it started and let DS continue.
zenoprax 5 hours ago [-]
What is your workload?
davedx 9 hours ago [-]
I have started phasing into DeepSeek v4 (Dwarfstar quant from Antirez) as my daily driver and it's going very well. It can one shot iOS apps on my Mac Studio, it's a little slow and sometimes needs retries but can definitely do medium difficulty real work for me.
I didn't try the last flash model because I would need to use SSD streaming (I have 128 GB), but the benches for this release are so compelling (and it using less tokens to get tasks done) it might be worth the throughput hit. I will probably give it a try when I have some downtime.
It feels very freeing to be doing useful work on a local model on my own hardware with my own coding harness. The TCO argument is starting to look compelling too.
kamranjon 8 hours ago [-]
Try the Qwen 3.8 flash next model on DwarfStar - you will be very surprised. I’ve been using the 4 bit quant almost exclusively after having DS v4 flash be my daily driver. Qwen is faster and seems to be much better at coding tasks.
ilaksh 7 hours ago [-]
This is a new model, not the same as a different one.
jononor 12 hours ago [-]
Above GLM 5.3, nice! That is a very capable model. I do wish that we will see some smaller "flash" models again though - running this one locally is tough (very costly).
LaurensBER 12 hours ago [-]
For comparison, close to Opus 5. Far behind Sol 6.1 and Opus 5.5.
Probably a pretty decent model for 90% of the usecases!
I've been doing a lot of hobby work with GLM 5.3 Flash and I can count the amount of times that I need a stronger model on two hands.
I have access to unlimited tokens at works and Opus is great but also often overkill if you know exactly what you need.
egeozcan 12 hours ago [-]
I use Opus for planning, through API on medium thinking, it doesn't cost anything significant and the rest can be happily done with deepseek or glm flash. Using sol 6.1 for review loops at the end. All running on pi.
A very complex task tends to cost like 10$ max. It's comparable to a subscription with enormous flexibility.
It's a steal.
cromka 10 hours ago [-]
Honestly, I don't know what people see in Sol 6.1. Opus 5.5 is so much more inteligent, as in proactive, avoiding stupid mistakes, where it contradicts itself, ignores the context. Sol 6.1 has a gold-fish memory, it's as annoying for me to work with as Opus 5 was.
ac29 2 hours ago [-]
I'd rank Sol 6.1 only slightly behind Opus 5.5 in intelligence and both significantly ahead of anything else I've used (though cheaper/faster models are totally fine for a lot of tasks). My only real annoyance is 6.1 Sol is one of the slowest models I've used, which does make Opus 5.5 more pleasant to use.
cjbgkagh 10 hours ago [-]
You can override the context length of Sol to 1M
joshstrange 9 hours ago [-]
Without this change I hated Sol and was burning tokens way faster due to all the forced compacting.
Since making this (obscure/hidden) change I enjoy Codex much more.
cjbgkagh 8 hours ago [-]
The work I do cannot fit in 256k so it was just relearning the same things over and over again while making zero progress. AFAIK the 1M burns tokens at twice the rate but I use Sol on medium as the work I'm doing now needs more memory than it needs intelligence and it's working great. I use Opus 5.5 for the stuff that needs stronger intelligence.
cromka 8 hours ago [-]
That's not actually the problem. It forgets the instructions from 15 minutes ago, without context compression involved in-between.
cjbgkagh 6 hours ago [-]
That has not been my experience after bumping it up to 1M. I do run a lot of agents in parallel ~10-16 and I actively babysit them so perhaps I'm just used to reminding the agents with things I've already told them. But I don't notice much of a difference between Sol 6.1 1M and Opus 5.5 1M
minraws 11 hours ago [-]
By next year we will likely see GLM 5.3 level performance in Qwen 4 MoE models that can run on most higher end consumer systems.
I don't think there is a reason to care about any of it, just get a few dollars on a few openrouter or similar platforms and just use the models for now, wait for cheaper models that are good enough for you to become available for your hardware.
Sure you might never see frontier performance on consumer hardware but do you really need that though? Does anyone? And if you ever do just get a 30-day sub for that work, and cancel it.
jononor 8 hours ago [-]
Yeah performance at a given compute budget will likely continue to improve.
We are running Qwen 3.8 27B FP8 with 4x 5060 16gb at the office for a small development team. It is doing pretty well for implementing backend and frontend tasks, and is already useful. In 6 and 12 months from how I expect it to get even better. Some planning is still done with a stronger model, but even that is maybe not strictly necessary.
minraws 5 hours ago [-]
Qwen 3.8 wasn't that nice in my experience Qwen series has lagged a lot but I think Qwen 4 would be better they cleaned up the architecture.
And we are likely to see many companies start building 27-32B MoE models custom built for use cases now that Rubin is going to make training costs much lower.
I expect training costs to get under 100k USD within a year for small models with another 100k maybe for RL.
I think just having all your own data from claude and stuff on your system that you can feed these models and have companies offer great base 27B models will be how it works.
Pragmata 12 hours ago [-]
Cant you run it on a pair of DGX spark? Sure it's expensive now, but at the initial retail price that was what, 8k in hardware? Not exactly unachievable
bashtoni 12 hours ago [-]
No, this is not a small model. I believe 4x Sparks is possible but 4.1 is pretty big for a flash model.
MiMo 2.6 Flash is the most capable model you can currently run on 2x Sparks without resorting to a quantised version of something.
Pragmata 12 hours ago [-]
I meant quantized. You can get an EXL3 quantized version thats almost the same performance.
bashtoni 10 hours ago [-]
My experience running quantised models is that they look the same at first but are all noticeably worse once the context size gets beyond anything trivial.
Pragmata 9 hours ago [-]
I've tried both 2bpw and 3bpw quants for QWEN3.8 27b, and while i do notice a difference in terms of higher rates of getting stuck in loops, they are both reasonably usable.
Are they as good as opus 5.5? No.
Are they about on par with opus 4.6? Yes.
The long run tasks i run seem to be about the same level of quality, though there are obvious differences in model styles, token budgets, etc....
liuliu 6 hours ago [-]
Still need 2 or 3 days to properly quant this. But it is really good model to run if you have 64GiB or larger RAM on Mac. On M5 Ultra, you get ~3400 tok/s for prompt processing and ~50 tok/s for token generation, quite usable state.
RGS1811 6 hours ago [-]
Forgive the ignorance, but how are you running a 763B parameter model on 64GB of RAM?
liuliu 5 hours ago [-]
SSD weights streaming. The actual weights is 552B, then engram.
Faithful to the original theme. Apropos. +1 on adding the prompt as long as it’s affordable and easy enough Simon, and not too distracting/noisy/time consuming all considered!
Wow. Is DS the only model that consistently puts one leg behind the frame? I don’t even remember Opus ever doing that.
simonw 5 hours ago [-]
Some of the most recent Claudes and GPTs have done that too, and Gemini has done it for a while.
bagacrap 7 hours ago [-]
The best bicycle is "low".
eleventen 6 hours ago [-]
[dead]
summarity 4 hours ago [-]
Getting a lot of errors from OpenRouter's endpoint "Failed to get response from the AI model; retried 5 times (total retry wait time: 60.71 seconds) Last error: 429 Provider return error"
It works when it works, but will probably be flaky AF for a few days.
700000 because there's no detail yet on the safe completion limit for most harnesses (OR lists 1M for both which makes no sense). COPILOT_OFFLINE enables all calls except to OR (no GH servers).
yipinwong 3 hours ago [-]
I haven't put this into test as much yet.
As a Luna6 proponent, this has a potential as it looks slightly more intelligent and at the similar price point.
gmbhgmbh 12 hours ago [-]
Thank you deepseek, we are eating good today.
sligbad 5 hours ago [-]
Once read, I think from G Huntley, "pick a model and stick with it," they have been making that very easy, daily driver since V4.
dw_arthur 6 hours ago [-]
I am a huge DeepSeek fan, but it cannot come close to Opus 5.5 on UI design. A $20 Claude subscription that I use some months and cancel the others along with Deepseek API is great.
8 hours ago [-]
dcchambers 8 hours ago [-]
At this point I am way more excited by DeepSeek releases than anything from OpenAI or Anthropic.
The speed and cost/intelligence ratio is just outrageous.
waximabbax 12 hours ago [-]
Looks very impressive especially considering the price and speed. Let's wait for AA to confirm how well their benchmarks hold up.
scrollop 10 hours ago [-]
You trust AA since the sol fiasco a month or two ago?
grosswait 9 hours ago [-]
What did I miss?
esafak 6 hours ago [-]
They updated their methodology when the new openai model didn't rate higher than the old one, or something like that.
mchusma 28 minutes ago [-]
I do t think it was a fiasco. I thought the updates were good. They should do more work on benchmarks. There has been good work on testing benchmarks for example to ensure they are accurate, and as issues arise they should change the benchmarks. The point of AA and Arena is trying to understand how to think about models.
waximabbax 9 hours ago [-]
[flagged]
frail_figure 12 hours ago [-]
Why not just try it yourself?
viraptor 12 hours ago [-]
It costs money to run serious tests. We're way past the time when you could get an idea of the new model in a couple of tricky prompts. Now I need to compare a whole resulting project to get a clear view. If someone else proves the benchmarks don't hold up in reality, then it saves us further tests.
abc42 4 hours ago [-]
Have security companies considered that these open models could be used as sleeper agents even when they're deployed outside of China? Is that a serious attack vector or more like science fiction?
halJordan 4 hours ago [-]
There are theoretical attacks involving malicious weights. But the risk profile is so outrageously in favor of them not doing it that you'd essentially have to be an anti-China conspiracy theorist to find it plausible, let alone likely.
risphere 12 hours ago [-]
The native web search api is 10x cheaper than OpenAIs. I hope they will release the web search api as a standalone API.
alex-moon 11 hours ago [-]
I may be missing something so apologies if I'm telling you something you already know but: there are plenty of web search APIs for agents - the Brave one is the one I use: https://brave.com/search/api/
mmmmbbbhb 11 hours ago [-]
Tavily one is free, too. Easy to use cli with a skill.
ytxm 11 hours ago [-]
I gave it a kick and got mixed results. For example, searching for a Microsoft product couldn't find its landing page, and searching for a niche open source package landed in the Debian repos for the top hits, but the home page was in the first 10 hits.
Lovely to see they're doing their own search though, I love how many folk are actively working on search clones at the moment.
I can't wait for a smaller moe dinstillation from this excellent model
nik736 12 hours ago [-]
Those are crazy numbers for a Flash model. Hopefully they can scale what they are doing to 4.1 Pro.
drewbitt 4 hours ago [-]
This is a great model. I know we are all looking for the next best thing, but I'd be pretty happy running this for awhile.
aizk 6 hours ago [-]
I use Opus 5.5 and swarms of about 50 deepseek models to reverse engineer old videos games. The scale is roughly 600k loc generated from pure asm, simply by knowing what the old compiler is. Truly staggering stuff.
why_is_my_floor 3 hours ago [-]
Registered just to ask you.... 50 instances? Which harness? How? Why? Can you post a video demonstration?
cedws 5 hours ago [-]
Could you please share your methodology?
hartator 6 hours ago [-]
What would be the best local harness to run this? It feels there are 1000s now.
wolttam 6 hours ago [-]
Exactly, there is no ”best.”
klntsky 6 hours ago [-]
Here's a small benchmark that compares the new checkout with the previous one:
At the beginning of the month I realized I had more tokens and more capabilities on Opencode at 8$/month via DS 4.1 flash, than I had on a 200$ account in June with the american providers.
Literally both more tokens and capabilities than Opus 4.8/GPT 5.5.
Even if you pay per token, you're still unlikely to outspend american providers.
Flere-Imsaho 9 hours ago [-]
I've been telling people this for a couple of months now, I'm actually struggling to use up all my tokens.
ilaksh 7 hours ago [-]
But this is a new, different model that just came out.
jimbob45 9 hours ago [-]
What does it matter if you’re not hitting your cap with OpenAI/Anthropic in the first place? This thread is apparently populated with the highest of powerusers running multiple OpenClaws. Us peasants aren’t concerned with meters or cost/token - just quality - and nobody comes close to OpenAI or Anthropic in that regard.
hgoel 8 hours ago [-]
Pretty funny to say "us peasants aren't concerned with ... cost/token", as if most people ("peasants") won't find it absolutely insane to be paying $200/mo for a subscription.
selcuka 6 hours ago [-]
Peasants don't pay for the subscription. The employer does.
bagacrap 7 hours ago [-]
How could that be considered insane for a professional tool?
epolanski 5 hours ago [-]
In southern Europe (Italy, Greece) that's well beyond 10% of the average pay.
And southern Europe isn't exactly the poorest region around.
sroussey 2 hours ago [-]
Why no Jinja-format chat template?
d2kx 6 hours ago [-]
The new model is amazing. Had it build a full Angular Material & CDK components showcase via DeepSeek Harness and it easily did the best job of any recent models I've seen.
throwfaraway135 12 hours ago [-]
Another big win for opensource AI.
BTW who would have thought China would be the champion of freedom and opensource in the AI arena, while US is fighting for corporate/government control.
Dah00n 11 hours ago [-]
Well, at least mostly everyone outside the US.
ReptileMan 11 hours ago [-]
Anyone that has observed China since the 90s.
There are different types of freedom and China's bet is that as long as they provide enough economic freedom the public will be ok with somewhat restricted social and political one.
InsideOutSanta 11 hours ago [-]
Yeah, I had a somewhat odd conversation with a Chinese acquaintance last year when she got to talking about how America sees China. Her point was that, "How am I not free? I can do whatever I want, go where I want, buy what I want. I can talk to you and say whatever I want; nobody is here listening to me."
The fact that she can't call Xi "Winnie the Pooh" on Douyin wasn't something that occurred to her, or maybe that she was aware of at all. I didn't ask. I don't like to get into these discussions when I'm in China.
computerex 10 hours ago [-]
There is no such thing as “free speech” anywhere. It’s all a spectrum and the Americans in particular are indoctrinated. It’s a red herring to distract from the real social issues. People in America have some of the worst healthcare in the world. But hey at least we have “free speech”.
foobar10000 9 hours ago [-]
Fixing healthcare or economic policies is typically an act of congress type of thing - not even an amendment. Large popular support - and it can be fixed. Fixing freedom of speech or the ability to vote at all - once it is gone - usually takes a price payed in blood. Sometimes rivers of it.
Citizens of Palm Beach county cannot voice their opposition to how their tax dollars are being spent. They rightly want that money to be invested locally, instead the County uses it to invest $1B in Israeli bonds, something that people widely oppose.
They first said that it's a budget meeting and Israeli bonds are a "policy matter". Then they started arresting people for speaking out against it. Then they started arresting anyone who applauded.
"Free speech" -> I spit on American "free speech". It's the most insidious and dishonest thing. At least the CCP doesn't PRETEND to give people rights that they simply don't have.
dzonga 8 minutes ago [-]
wish hn allowed reposts just to reiterate this point.
the U.S allows "free speech" if it's inconsequential.
InsideOutSanta 5 hours ago [-]
Socialized healthcare does have large popular support, though. Lots of things have large popular support in the US and still don't get done.
gWPVhyxPHqvk 7 hours ago [-]
I can't call AI "AI" without being termed an "enemy" by the President.
ngl999 8 hours ago [-]
That economic freedom is a fantasy fabricated so that the king can rob people fortune created by the themselves in the name of greater good.
ngl999 11 hours ago [-]
That's an image China wants the rest of the world to believe. Towards inside it still fits the typical stereotype.
risphere 12 hours ago [-]
It's better than GLM 5.3 and Kimi K3 and way cheaper.
slopinthebag 11 hours ago [-]
that's honestly insane. it's like the go-to for when you don't want to use opus 5.5/sol 6.1
ngl999 11 hours ago [-]
The go-to is a local model.
gentlewater 9 hours ago [-]
Limp-to, maybe.
ngl999 8 hours ago [-]
With Strata, running GLM 5.3 is possible.
swingboy 8 hours ago [-]
Does DeepSeek provide the inference code along with the weights? I read here recently that for models where only the weights are released, providers have to implement which could be different than what the labs themselves use.
petu 5 hours ago [-]
There's basic reference inference code released with the weights, yes.
> providers have to implement which could be different than what the labs themselves use.
I'd imagine (most) providers just take implementation by vLLM/SGLang.
abdallah-khalil 8 hours ago [-]
I wonder how you would be able to reliably rely on a model like that for agentic work, even for implementation only after careful planning, how are you making sure you are not wasting tokens reviewing and correcting it over and over again ?
nickludlam 11 hours ago [-]
This and (the not quite yet open) Kimi K2.8 are my main coding engines, and I find them incredibly cost efficient. I find Deepseek in particular is really good with Svelte work.
Right now I use each of them in their own respective coding harnesses, deepseek-harness and kimi-code, but I do wonder what they are like inside something like opencode.
dcl 10 hours ago [-]
Very keen to try this out tonight. What coding harness do people like to use with these models?
ghboo0927 9 hours ago [-]
You can stick with Claude Code if you're already using it. DeepSeek has an Anthropic-compatible endpoint, so you just need to set ANTHROPIC_BASE_URL=https://api.deepseek.com/anthropic and ANTHROPIC_AUTH_TOKEN to your DeepSeek API key.
belluxx 8 hours ago [-]
Pi is very good with open weight models (proprietary ones too)
verdverm 7 hours ago [-]
Pi if you're a minimalist
OpenCode if you want a good, opinionated setup
vintermann 11 hours ago [-]
I'd never heard of the BabyVision benchmark they do so well on. Pretty interesting stuff:
Is it already updated to the newest version on Opencode?
nirav72 9 hours ago [-]
Yes. It’s actually free to use at the moment. Of course with a quota.
handfuloflight 12 hours ago [-]
Is it coming to OpenCode et al?
kzrdude 11 hours ago [-]
Presumably. The current opencode slug for the model is just 'deepseek-flash' suggesting they will just update that one going forward, not keeping versions in parallel.
opengears 12 hours ago [-]
and do we know which version runs on opencode at the moment (on the free and on the paid version), is there a way to find out?
swiftcoder 11 hours ago [-]
The only way I'm aware of is to check their twitter feed. They moved to Deepseek v4.1 flash in September
opengears 10 hours ago [-]
sure, but which version are they running. they could be running an older revision
kzrdude 3 hours ago [-]
Just yesterday there was just one public revision of 4.1, and they listed they were using 'Deepseek v4.1 flash'. I assume they will update their website if they update the model version (and use the version in the name).
SublimePeace 12 hours ago [-]
[dead]
hmontazeri 11 hours ago [-]
My favorite model just got better. Gotta love what deepseek is doing
johnnyApplePRNG 4 hours ago [-]
And Christmas comes early this year.
DeepSeek v4.1 Flash was a beast.
It was already cheaper and more powerful than Haiku 5.5 which was released like a full month after it... by a trillion dollar american "frontier" company.
Can't wait to see what this one has in store.
floooof 12 hours ago [-]
they must've been using this since 2-3 days when it became free again in OpenCode, it's noticeable smarter, beats GLM
sharktheone 11 hours ago [-]
beating K3 and GLM-5.3 is kinda insane
bashtoni 12 hours ago [-]
"a minor update" they say before showing off benchmarks that display a substantial improvement.
clx75 10 hours ago [-]
Probably a week ago someone posted a thread with the title "Why isn't the industry freaking out about DeepSeek 4.1 Flash?"
I have been intrigued about Chinese models for a long time, but never tried anything except an early Qwen. My daily driver was Luna, with occasional elevation to Terra or Sol - all on 5.6 as I found the output of 6 jarringly incomprehensible.
I still had 95 USD on my OpenRouter account, so I thought I would give DeepSeek Flash 4.1 a try.
I think now I can understand the person who created that thread.
Here is the setup I settled on, after a lot of refactoring and calibration of the workflow:
I have a "plan" prompt which explains to the agent (Luna) that I want to have a discussion about an idea I have in mind. The agent should use the Socratic method to pull out all the necessary info from me using pointed questions. When the agent feels it has a complete picture, it should elevate to a higher level model (Sol), and ask its review. If Sol has complaints, Luna keeps asking me until the points raised by Sol are clarified. The review rounds with Sol continue until Sol says "ready to implement".
At this point Luna creates four files in a directory I specify:
1. PLAN.md: the implementation plan with all the details that came out from the design discussion
2. PHASES.md: implementation phases
3. DECISIONS.md: design decisions (this serves the same role as ADRs aka. architectural decision records)
4. DIARY.md: append-only log of what happened during implementation
Files 2-4 are written by the implementing agent. Luna only adds headers to explain the purpose of the files.
Once these files are there, I start up a new Pi session, switch to Deepseek 4.1 Flash and then point it to this plan folder.
And then it goes brrrrr... :-)
Here is what I implemented in the past week using this method:
1. A capture/analysis/decompilation pipeline for C64 demos: I ask the agent to start a selected demo through VICE, and say "on" or "off" when I want it to start/stop capture. The capture process uses VICE's builtin trace functionality: the trace log is piped into Clojure where it is saved into an optimized binary format (chunks of trace events). Once I have everything captured, I unleash my analysis pipeline which checks the write patterns of the executed code: what it wrote (VIC, SID, CIA, memory) and when (rasterline, cycle). Then it splits the execution trace into segments by type deduced from the write patterns (decruncher, loader, raster, music) and then decompiles each segment into both traditional ASM files and a s-exp based syntax which roundtrips back into the in-memory representation. Once I have the results of the analysis pipeline, I can tell the agent to analyze any demopart and it can explain how the effects are built down to the tiniest timing detail. As a first test, I asked it to create a clean-room implementation of Fairlight's legendary intro and two days later I had it, with everything in sexp assembly, including the music routine and its data. (The reason it took so long was that this was the first decomp and it provided a lot of feedback to the pipeline development.) Finally I had it write an assembler, linker and packager which creates a PRG from the assembled and linked artifact, then runs it through VICE. Done.
2. A DSP compiler which lets me compile sexp forms of a C-like DSP language into native DSP kernels running on the JVM, JS and WASM. Currently I have about 600 tests which verify that the behavior of the three targets matches that of a reference interpreter written in Clojure. I have a full numeric tower with i32, f32, f64, support for arrays and structs, typical control flow constructs, and a library of DSP building blocks like oscillators, filters, LFOs, delays and a chorus effect. By the time this is ready (end of the weekend?), I will be able to build synthesizers like Synth1, Surge XT or Vital in Clojure/Script, compile the DSP kernels in the browser, choosing between JS or WASM backends, driving the kernels via AudioWorklets and sequencing them from the host language.
There are two power tools at play here:
1. Deepseek Flash 4.1
2. Clojure and ClojureScript
Deepseek is a BEAST. It just goes on and delivers, phase after phase. What it needs: clear instructions - this is covered by the planning process quite well, but I still find it needs some steering from time to time (the right nudget of wisdom dropped into its thought stream at the right moment works wonders)
And Clojure... well. That article PG wrote about LISP (Beating the averages): what I witness now proves all of those claims.
The agent LOVES Clojure. Especially the REPL (not so much the parentheses).
Winning strategy: give it two tools: start_jvm and clojure_eval. Implement everything else it may need - tools to start up HTTP servers, compile ClojureScript, add dependencies, capture a C64 demo, run Playwright via spel, etc. - as lightweight Clojure namespaces which provide APIs to all these functionality. Let these namespaces be thin: the namespace and the functions therein shall have docstrings which tell the agent what the functions do, but the functions themselves shall be lightweight proxies to the real implementations in sub-namespaces. Then point the agent to these top-level API namespaces via your AGENTS.md. Bam, instant discoverability with minimal context usage. It will do EVERYTHING through clojure_eval and the round-trip time will be phenomenal, a perfect match to the raw speed of the agent.
...
Now all I need to figure out is what will I do when all my dreams become manifest in flesh.
Qiu_Zhanxuan 9 hours ago [-]
Isn't there a lot of overlap between PLAN, PHASES and DECISION that pollutes the context ? Whereas a simple PLAN.MD to put the harness on track and an ARCHITECTURE as a single source of truth to prevent it go offtrack would suffice and gives it more space for higher level of reasoning ?
clx75 9 hours ago [-]
These files came to be after I've seen Deepseek create them for itself to track progress.
Then I turned what Deepseek did into an upfront policy.
This seems to work quite well generally: watch the agent as it works, and think what could be provided to make its life as easy as possible
ilaksh 7 hours ago [-]
Have you thoroughly tested a slightly simpler workflow with one less stage but a frontier model doing the initial planning? Luna is amazing but it's a deliberate trade off designed for speed and cost savings. You can also give them a rule about speaking clearly.
clx75 4 hours ago [-]
The idea behind using Luna was cost-optimization.
I wrote a Pi extension called "model-escalation" which lets the model request an automatic switch to a smarter model for the next turn if it thinks the problem it is struggling with is too complex or if the user explicitly asks it to do so.
With this extension in hand, I could split the work between Luna and Sol, resulting in a ~95%-5% split. I don't have to switch to Sol when review time comes, Luna does it automatically. Sol tells its remarks, then Luna gets the control back and continues the back&forth (if there are still complaints).
rs_rs_rs_rs_rs 9 hours ago [-]
Pretty cool, thanks for sharing.
sourcecodeplz 6 hours ago [-]
at this point there are 100s of benchmarks.
so AI labs can just pick which to show
jordemort 7 hours ago [-]
oh is “Flash” a cool sounding word again since Adobe abandoned it?
npn 12 hours ago [-]
So this is the reason for the crash a few days ago.
dgellow 12 hours ago [-]
What crash?
npn 12 hours ago [-]
Deepseek servers went unavailable for 5 hours.
They compensated that by rewarding the previous week usage as credit though. Pretty nice.
That's way cheaper than openai and other web search providers. I have no doubt that AI demand justifies all the compute money big tech is spending now, but I also think there are so many over valued VC funded companies that are going to crash in the next few years.
vivzkestrel 6 hours ago [-]
- how good is it at reversing a game exe file?
objektif 7 hours ago [-]
Anyone using DS as CLI coding agent which harness do you recommend? Is there anything as good as CC/Codex?
drewbitt 4 hours ago [-]
I really like pi, though it does require some time in setting it up. But it has greatly reduced my token spend. The relevant Deepseek Harness https://www.deepseek.com/en/harness/ I hear is also good and popular.
drewnick 6 hours ago [-]
I use deepseek via fireworks using Claude code.
When I type deepseek on my CLI it launches Claude with my fireworks API key. Works very well and feels almost free.
jimmydoe 4 hours ago [-]
PSA Deepseek train on your session if you use their endpoint and/or harness.
I'm a communist so I'm fine, but you may not be, so be aware
lilod 3 hours ago [-]
PSA OpenAI&Anthropic train on your session if you use their endpoint and/or harness.
I'm an American! so I'm fine, but you may not be, so be aware
flowskill 5 hours ago [-]
[flagged]
Jeeetendra 5 hours ago [-]
[flagged]
Klovy 10 hours ago [-]
[dead]
SublimePeace 12 hours ago [-]
So is this the first model that passed China's new export controls introduced yesterday?[1] It goes live November 15, but temporary pre-registration requirements took effect immediately after the announcement, ~20h-ish ago.
Presumably they registered, but that doesn't mean the model passed through export review. It just means that some bureaucrat now has the opportunity to check the product characteristics they reported and decide whether that kind of thing should be allowed for export or not. (Though with the weights out in the open, that's maybe a bit pointless.)
xutwa 10 hours ago [-]
[flagged]
jdw64 11 hours ago [-]
[dead]
silasvane 11 hours ago [-]
[flagged]
josharsh 8 hours ago [-]
Try adding a new comment
m00dy 12 hours ago [-]
We're in a crisis
ngl999 11 hours ago [-]
Censored, no surprise
leopoldcongo 8 hours ago [-]
Oh mince, mon immense meurtre des humains congois dans le fruit
freakynit 13 hours ago [-]
Those benchmarks can't possibly be real, right? Right? <insert padme 4-panel meme here>
logicchains 12 hours ago [-]
At this rate the frontier labs will be Anthropic and DeepSeek, with OpenAI struggling to keep up.
A_D_E_P_T 12 hours ago [-]
OpenAI's models -- and even Google's Argon -- have particular niches where they shine. For GPT-6/6.1, it's 3D modeling; Astra is hands-down the best at making .step files, Blender files, etc. For Argon, it's natural language writing and everything that hooks up to Google, e.g. search and maps-based itinerary planning.
Anthropic and DeepSeek (+ GLM) are definitely solving coding, though!
They're all quite different tools.
Kurtz79 11 hours ago [-]
Artificial Analysis recently released a dedicated 3D benchmark, where Astra lags behind both Opus and Sonnet 5.5 (and yes, open weight models seem to be quite far behind).
For me it's large files in Blender (in some cases >400MB), mostly, where Astra excels. I gave it a look, but I don't know if the benchmark encompasses that sort of thing.
.step files are simpler pieces of straightforward code, so it makes sense that Opus and Sonnet 5.5 do very well...
swiftcoder 11 hours ago [-]
its unfortunate they didn't include deepseek in the initial batch of benchmarks
11 hours ago [-]
freakynit 12 hours ago [-]
I believe these are the last sets of super-high-end models available to public (open or closed).. these companies probably will now start to withhold top-of-the-line models for themselves, governments, and their super-high-paying partners only.
A_D_E_P_T 12 hours ago [-]
That hasn't been the way to bet. DeepSeek and the other Chinese firms show no signs of slowing down, so if OAI and Anthropic halt releases and "pace the frontier" they'll just fall behind. (And there's a chance that high-end AI will become fully commoditized, which suits DeepSeek just fine.)
Besides, Fable 5.5 is reportedly releasing within the next few days, probably on Tuesday...
girvo 10 hours ago [-]
China just announced tightened export controls on AI models, for what it's worth.
skeledrew 7 hours ago [-]
I really, REALLY hope this is a joke.
stymaar 12 hours ago [-]
News from a near future:
Here's How Distill APT Used McKinsey's Private Access To Top Anthropic Model To Help The Chinese Keep Up With The Us Top IA Labs Despite Access Restrictions
ReptileMan 12 hours ago [-]
We have the weights, we have the papers, nothing preventing development on this foundation.
hgoel 8 hours ago [-]
Except compute
ReptileMan 8 hours ago [-]
Do you think we are near the theoretical maximums of how much model we cram into 20B?
hgoel 6 hours ago [-]
I don't consider myself qualified to make that call, though I believe there's plenty of room for improvement. But I don't mean inference compute, which is fairly accessible for well-off enthusiasts even now. Training is a lot more expensive though.
ReptileMan 1 hours ago [-]
Back in the day we had seti@home, prime95 and fold@home. We will make it work.
slopinthebag 12 hours ago [-]
idk, sol 6.1 is both cheap and capable. i've been using it exclusively, i don't need to care about usage, and it's really smart.
yes maybe opus 5.5 is stronger and flash is cheaper, but 6.1 strikes a good balance imo.
computerex 10 hours ago [-]
OpenAI models don’t come close to competing with deepseek in cost quality ratio. I have a $20 plus plan and I run out of my 5h limit in literal minutes, every tick of the harness is like 10% of my 5h limit.
You can in contrast get far more done with $20 worth of deepseek api spend. No comparison.
ReptileMan 12 hours ago [-]
i have a feeling that Sol is just Astra low, but with lowest possible priority on the compute.
WASDx 11 hours ago [-]
I believe it's Astra quantized. It was briefly named astra-lite.
Rendered at 21:13:12 GMT+0000 (Coordinated Universal Time) with Vercel.
First, it's the tok/s and TTFT from providers. Deepseek blazes through work - at quite good quality - and you don't find yourself waiting for your agents to finish.
Second is the openness. Being able to see the CoT and not being randomly blocked for cyber review. You're never wondering if it's stuck or if it will randomly fail. Combined with the great cost value.. My next subscription will probably be Z.ai
Some people would say that you don't need this at all with the frontier llms. But when extending existing software or writing software that fits into an existing ecosystem, I find I still need to offer a lot of guidance. And it's better that the context window isn't flooded with code that was reverted after I looked at it.
Hit the nail on the head. Development methodologies pivoting at the whim of frontier models have been one of the things that have been worrying me as of late.
As long as the API is private or not dependent on by automated systems and you have good test coverage, you can get away with bad code IMO since you can always refactor. If it looks stupid but it works (and can be refactored/fixed/improved later if needed) it aint stupid.
In a way, that’s the situation today. You can pay an experienced developer $$$$ to do it right, or you can outsource it and pay $$ but pay extra for more layers of review, have lots of unfixed bugs and more tech debt.
You are proposing that instead we pay the frontier model to clean it up. If it can, I expect it to cost somewhere in the neighborhood of an experienced dev because that’s the alternative. That’s the way the frontier AI companies will extracting the value of the work from you.
But there's two ways this could be true: Frontier models costs rise, or (more likely) experience dev costs fall
They already did the bare minimum allocation to both despite engineering screaming at them.
I highly doubt executives are going to accept slower release and sale cycles in order to provide better support.
If anything, I expect this trend to accelerate. I’m imagining the opposite, a plethora of AI slop with increasingly burned-out engineers.
Sales are out of their control.
If there’s a market for quality and you don’t have it, sales are going down no matter what the PHB wants.
If there’s not, watch out for the vibe-coded competitor.
yes!So it's not just me. In terms of how intelligent they want to be OpenAI is at the top, then Claude. And actually when I was playing with Sol it meant that many tasks it would just try to do something else because it thought I don't know what I want. Even trying to nudge it back in the right direction wouldn't work.
I guess the models just have the cultures of their creatures.
DS is miles better than GLM in this regard. I wanted to add that as PC is planning to go to GLM next.
Keeps repeating things I settled as accepted or rejected. But what really gets on my nerves? The language it uses – that aweful, useless typical LLM languages! No AGENTS.md instruction, no per session instruction, no just two-prompts-prior instruction seems to work, hell sometimes instruction regarding that in same prompt doesn't work. GOOD/BAD example along with instruction don't work. That wastes time and zones you out! Not to mention the fatigue of to and fro. DS has been working much better. Hell Gemini 3.1 Pro works so much better than GLM. I don't have extended experience with OpenAI and Anthromic models but the free claide.ai works quite well and better than GLM 5.3 (not even flash). Albeit I must say I rarely use claude.ai for coding, but technical tasks? All the time!
GLM's best response: "No excuse. My fault. You exactly asked me not to do exactly that and so did the AGENTS.md. I failed". Love it. Except that if I press I will get that response every 5 prompts.
It would just loop on things and go down rabbit holes more. DS flash has been so consistently good I've kinda settled on it for 90% of my work.
I still use adversarial review for bigger changes where I want to make sure any issues are caught early, but I genuinely feel as tho if no new models ever get made I'd be fine with just using DS forever.
I like giving precise instructions,”update function xx to support input yy, add tests”. There is no reason for 10 turns and 5 minutes of waiting.
DS just handles ambiguity and my bursts of detail with much more grace. I'm only using "max effort" and the CoT is reasonable compared to GLM.
This really depends on the provider, it's a very fast model with ours
Wait... you just spent 3 paragraphs singing the praises of DS... and then you say you're going to subscribe to the one that makes GLM. ?
(I do tend to agree with you, though I tend to favor GLM-5.3-flash over DS 4.1 flash.)
debugging reasoning traces more effectively seems useful to find prompt issues writing custom harnesses even if it runs on stronger model later
It doesn’t have to be better, it just had to be nearly equivalent. I’ve been doing a lot of vulnerability work lately (trying to get ahead of the bots finding exploits in our code) and the frontier models feel like a chaperone at a church dance: get too close and they show up with the ruler and enforce the safety margin. Using deepseek and glm and qwen, I’ve gotten nearly equivalent results without the constraints. I still use frontier models for things but outside of a company environment, I’m happy to spend 1/10 the money, get the same results, and not have try and trick the AI into working.
Without getting too much into politics; over the past several decades, one country is going around starting wars, regime changes and other interventionism, or initiating economic warfare (Huawei sanctions because they were getting too competitive to US companies; GPU restrictions; tariffs; etc), and that's not one administration: it's US policy over the past few decades.
https://ourworldindata.org/grapher/human-rights-index-vdem
It's kinda like meeting someone on the street who's protesting about animal cruelty in slaughterhouses, slyly handing them a chart showing them the nutrition facts of beef, and then walking off without another word as though you've settled your case.
Like, I get the point you're trying to make, but I hope you're aware it's a non-sequitur in context?
Your hope should have been that amelius was not aware that it's a non-sequitur, because that is correctable. But then they kept posting and removed all doubt.
People like to bring up the Uyghurs immediately, but never really have the same smoke for the US. Also, do we include the prison population in human rights? Do we include access to healthcare? What about systems perpetuating poverty like lack of access to public transportation?
To pre-emptively be clear on my stance or potential bias, I stand by no country in the world. I was born in Iran, and my parents left when I was young to the US because they believed in the American Dream. The irony being that the dominos of why they left were initiated by the US and UK. And long before Trump was elected, but certainly immediately afterwards, I decided to leave the US once I had the means. (Also because of the lack of public transit, the $100k medical bills after an accident, being punched by a homeless person, and having my possessions stolen repeatedly and the cops giving me a :shrug:). I moved to Japan, where I experienced blatant racism for the first time. I moved to Hong Kong (and tbh no real complaints so far), but I am technically subject to the freedom of speech constraints on China.
I have no allegiance to any country or specific people. My allegiance is to all living beings.
And I don't care if they're reputable, I will look at the methodology and make my own conclusion either way. Appeals to authority are not a substitute for critical thinking.
No lessons to take from the US.
PS. https://en.wikipedia.org/wiki/Foreign_interventions_by_the_U...
I know the US thinks only its citizens are human, so "The United States has been involved in hundreds of interventions in foreign countries throughout its history, engaging in nearly 500 military interventions between 1776 and 2026, with half of these operations occurring since 1950 and over 25% occurring in the post-Cold War period” is not probably part of the reputable storytelling
If they actually said something, it would be much less effective.
> We're not talking about a few % difference here.
How may freedom percent is it again? Do you lose 1% or 20% for failing to allow foreign ownership of utilities? How many percent do you gain for stopping Russian misinformation?
I'm not going to discuss it further if you don't have anything substantial to bring to the table.
edit: wording
https://www.prisonstudies.org/world-prison-data/highest-lowe...
https://www.theguardian.com/us-news/2022/sep/27/slavery-loop...
In Arkansas, agricultural work accounted for 17% of all prison labor assignments in 2021. https://www.prisonlegalnews.org/media/publications/Captive_L...
Yes, people have put thought into this. This is why I trust institutions and not random posters on the internet.
Just look at Russia - it's score is highest in the 90s - the most corrupt and destitute time in its modern history, also happens to be when it was deemed somewhat friendly to US and friends.
> Have you ever wondered why Manus founders gave up billions of dollars from Meta and “voluntarily” moved back to Beijing?
This country wouldn't be such a shithole if we were able to bring the wealthy to heel. I suspect most people on earth see China as the more competently governed country. Understandably, this forum tends to select for people who view private investment positively, but this is clearly insufficient by itself to produce functional societies.
[0] https://openrouter.ai/deepseek/deepseek-v4.1-flash
(The badges next to companies indicate their privacy terms, i.e. green/yellow/red)
The "green" badges explicitly say the opposite:
> "Private: this provider does not train on prompts and does not retain prompt data."
I.e. for the example of Fireworks, this is the precise language they use to describe ZDR:
> "More technically: prompt and generation data exist only in volatile memory for the duration of the request. If prompt caching is active, some prompt data (and associated KV caches) can be stored in volatile memory for several minutes. In either case, prompt and generation data are not logged into any persistent storage."
https://docs.fireworks.ai/guides/security_compliance/data_ha...
Plus only one country has threatened to annex mine and it wasn't China.
The economic sovereignty of any nation, but especially smaller ones like canada and denmark, is harmed by sending our money out of the country when there are options available in country.
I respectfully disagree. I subscribe to the comparative advantage economic principle, so I'm fine with international trade.
The 'clean power' would factor in a well, but I haven't really looked in to it. I know China is installing a ton of renewable and has a carbon market while Canada's building a new pipeline and building Alberta data centres running on natural gas, so I'm not willing to take on faith that switching is cleaner.
Also, re: power. I said canada has lots of cheap power, clean was your word.
The unfortunate truth behind at least the solar PV boom in China is that it's driven in large part by the exploitation of Uyghurs in the Xinjiang region. One of the reasons they can sustain the pace they're going at is because while nowadays PV modules exports increasingly gravitate towards offshore fabs (Vietnam, Malaysia), domestically all the biggest PV players make full use of modern slavery within Xinjiang's re-education camps.
more on the topic: https://www.shu.ac.uk/-/media/home/research/helena-kennedy-c...
It might be a minor nitpick, but that part is just not how the macroeconomic principle works. Abundance of a good/service within a country is irrelevant to the concept of a comparative advantage - this is counter-intuitive but but that was David Ricardo's entire point. It's not about whether production is more efficient domestically, it's whether comparative allocation of resources between multiple countries is more efficient by specialization within the different goods.
Even if you can produce "good 1" cheaper in Country A vs Country B, if Country A can instead produce "good 2" that Country B cannot, it's better for Country A to produce "good 2" domestically and import "good 1".
Now, I still agree with the original notion. It's unnecessarily risky to use services from "democratically-challenged" nations (especially imperialist ones), when safer options are available. But there's no need to twist macro 101 concepts to justify that view. Modern trade policy takes more into account than basic market efficiency.
(But I'd concede that in the field of genocide China doesn't come up as bad)
https://www.edenai.co/
e.g. https://www.edenai.co/models/deepseek-v4-1-flash
I feel like I’m getting good value out of my subscription and they have the cheapest GLM-5.3 API rates I could find in Europe. I moved to them recently from Mistral for the better prices.
They do have a slightly different daily inference capacity allowance, but it’s actually not too bad once used to it. I was forced to up my game and figure out what GLM-5.3 Flash and Deepseek-4.1 Flash could actually do for me, rather than just throwing everything at GLM-5.3. Quite happily chugging along with a nice balance across them now.
I am hoping Melious make the new DS 4.1 Flash 1017 available soonest.
[1] https://melious.ai
Dont assume that is how your model decides...
https://arxiv.org/abs/2305.04388
https://arxiv.org/abs/2307.13702
https://arxiv.org/abs/2503.08679
I can't tell if this is a really human thing to do, or if it's just a sycophantic thing to do when your master likes a good story.
I love COT and gives me a good idea about the thought process. Sure it doesn’t work always
Both OpenAI and Anthropic hides so much of that, that you don't really know if it misunderstood something or you got something wrong, until all the turns are complete or you directly see tool calls that implicitly tells you something is wrong.
You don't need to read any papers to see this effect concretely when developing together with LLMs.
DeepSeek feels like an excellent sparring partner. The others feel like mind readers.
I don't have to worry about any complex context engineering / multi agent stuff if I am using DeepSeek because the sequential stuff is fast enough. I don't have to bother about touching a million context length because its cheap enough.
Where it seems to lag behind is 3d, computer use, motion graphics, design but the initial demos seem like the vision model has improved substantially.
Is DeepSeek: DeepSeek v4.1 Flash 1017 any better?
[1] - https://www.youtube.com/watch?v=P4dTq4X8bqk
please don't subject yourself to this. z.ai subscriptions are not a good value. just pay API rates, or use a subscription like opencode go.
I always find DS or Qwen to be very spot on on audit changes or plans for just a few cents.
If so OpenCode Go looks good and includes DeepSeek models (yet to try myself).
It is very capable for a lot of tasks, not only coding like the other open models.
No, I don't care about license provenance for all the components of a 30 line script that i'm using in my house, for myself to sync up some folders. No, i'm not going to find and archive the licenses for all the previous projects leading to this for future legal disclosure.
Yes, I own the DVD for the movie i'm transcoding. No I don't want to talk about the legality of rebroadcast.
Deepseek (and most chinese models as a whole) don't care . oAI and Anthropic models want to make it point #1.
... which is extra hilarious knowing the laws broken to create the damn models in the first place.
there's a literal meme about this floating around the harness/AI chats for the past few months[0]
[0]: https://i.ibb.co/SwH4Sgwq/796779070-28483090404651613-920066...
Just to test, will GLM – hosted by an infra provider other than Z.AI – also stop answering if I asked controversial questions from the pov of its country of origin? Or third party infra providers can perform some unhinging on the model before hosting? Or actually the blocking happens even before the question reaches the LLMs in that country?
(Note: my paid LLM access at this point are only via DS and GLM subs - 90-95% usage; and a free Gemini Pro access. I hope that adds some cred that I am not trying to take potshots at the their country of origin).
I usually default to ds, and if it gets stuck try mimo but usually just for fire and forget tasks. After a bit I come back and see what it did.
I had a bad experience with MiMo from Xiaomi. I had it trigger unsafe content blocks while fixing visual bugs in a completely vanilla space game it just wrote from scratch in the same session. It also got triggered for changes in some other benign greenfield app.
Wait wut? You do realize that they are two different companies, right?
The Fable is the worst offender, and it is not purely Anthropic's fault.
Anthropic, whether Opus 5.5 or Fable, frequently will review for security, and the classifiers fire mid-way while it's fixing something. Authentication and credential related code, including implementation, also trigger safeguards.
Earlier today, I hit what appears to be a sticky "reasoning_extraction" block when attempting to reproduce a LLM paper at small scale, and I asked it ~"tell me more about the idea [X] you considered but dropped". I'm not sure how it works or how long it lasts, but Opus 5.5 has refused to do technical LLM work for me now, even in completely new sessions.
It reduces the speed and tends to overthink sometimes which is really annoying. For programming, 4.1/high is the bread and butter in my daily work.
It's only for long running/very difficult cases that the differences are here, and they are small.
Long-term & software engineering fronts: I hear occasional railing against “US hegemony”. Anyone concerned that if a new tech gives rise to a different country, they’ll become the source of ire instead? (This isn’t my field, at all.)
So I go with feeling, and that feeling says that China is worse. The feeling is partially supported by the fact that China is softly backing Russia in its attack against the west.
Trump's USA is obviously completely horrible, but he is also in large part a product of Russian influence, which again is part of the larger block in which China resides.
And China is not really supporting Russia, they make money off the war and want to keep it going as long as possible so both Russia and Ukraine become weak and more open to their influence. Is it evil? Absolutely, but you can't compare them to USA when Trump is actively doing regime change operations, deporting its own citizens and putting sanctions on the ICC.
Chinese communists want to stay in power at all costs but America wants to expand its power into the whole world. It's not the same level of danger at all.
note that the volume of EU and US support to Ukraine is obviously calibrated to the same goal.
Yes, yes they are.
https://en.wikipedia.org/wiki/China_and_the_Russo-Ukrainian_...
Trump’s a smelly orange shit but the US at least pretends to have data privacy protections and we can’t legally compel companies to have back doors… yet. I think. It’s very hard to keep up with all the nonsense these days.
In a post-Snowden world where the existence of PRISM is no longer a secret, I'm not sure how folks can keep stating this with a straight face
1. They, and many other experts, have been saying the same thing since well before the current paradigm existed. 2. There is nothing about regulation that is required to give them an advantage; it’s a fallacy to suggest “regulation = advantage” 3. It would be preferable to argue the facts (is it or is it not dangerous? Why or why not?) than conspire as to why they’re stating what they and plenty of others have been saying for decades
1. He's made many posts about how he thinks "dangerous" models are bad (https://www.anthropic.com/news/position-open-weights-models)
2. He writes posts proving Chinese open weight models are "dangerous" (https://insightsintegration.com/anthropic-warns-of-advanced-...)
3. He talks about about how he wants stronger govt regulation of AI (https://www-cdn.abcnews.com/Business/exclusive-anthropic-ceo...), and explicitly mentions he does not trust China at all and doesn't want them to have Mythos.
Do the math: 1 + 2 + 3 = he wants to regulate/ban the Chinese open weights.
Of course, Anthropic and OpenAI will then write posts about how their own models are dangerous - but that's okay, they're the good guys.
He's completely transparently campaigning for regulation. It must be very frustrating to him that the Trump admin is completely non-responsive. He probably thought Anthropic would have the whole market stitched up and water tight by now.
[0] https://www.anthropic.com/legal/aup
OpenAI and Anthropic aren’t even slightly worried about DeepSeek.
They are showing this new version scoring significantly higher across multiple coding benchmarks, beating Sol 5.6 (6.1 is the latest) across 10/11 benchmarks.
I am going back to DeepSeek for writing code. I was trying out using Sol and liking the result, but this should close a lot of that gap. I use Opus/Sol for an implementation plan and code review also use them for grilling. DeepSeek is also running verifications.
i let 4 different agents review the same dirty code base (200+ files changed, c++, game engine):
- deepseek v4.1 flash via deepseek API: took 20m to find one p1 issue that was relevant and a p2 issue that was irrelevant
- glm 5.3 flash NVFP4 via TP2 DGX Sparks: took 1h 5m to find a p3 documentation issue
- gpt 5.6 sol: took 5m30s for one p1 and one p2 issue. both relevant
- gpt 6.1 sol: took 4m30s for two p1 and one p2 issue. both relevant.
Worth to mention: none of those findings overlapped.
I let deepseek v4.1 flash and gpt 6.1 sol both plan fixes for the summary of the findings. in this particular scenario: gpt 6.1 sol planned to increase a buffer size from 128 to 256 to fit the 191 elements that blew past a test scenario. it included some headroom. deepseek v4.1 flash on the other hand decided to make it exactly 191 to satisfy the test, for example.
The TPS decode on deepseek is impressive. I never had a second / feeling of being left aone and though "damn this thing is working". Despite all my efforts, it took ~4x longer in a review, found less and planned worse than GPT 6.1 Sol. Wall clock time. I don't have token counts for comparison. If I were to grade those models from 1-10 (10 = top tier GG), I'd give deepseek a solid 6.5 and 6.1 sol a 7.5-8.0 maybe.
New model comes out and someone says, "it can (or can't) draw ducks on bikes" or some esoteric thing. But it's not enough statistical power to claim anything other than a personal anecdote.
I got a flat tire in downtown today. Therefore, driving in downtown causes flat tires.
For another, the dependence on a random seed is just one example of how you can get different behavior. You could just as well get different results due to e.g. a tiny difference in prompt wording or punctuation or whitespace.
If a model passes some test on 70% of random seeds, and fails on the other 30%, then knowing the rough probability of success is much more useful than knowing one random sample of the outcome.
And empirically this kind of probabilistic success is quite common, because many LLM benchmarks report "pass@k" success rates that are much higher than the "pass@1" success rate on a single attempt.
But try it on high instead of max if possible. max is known for being overly verbose to the point of being detrimental compared to high at times.
For example Simmons svg pelican took 11 minutes on max and 1 minute on high. And they are comparable.
I too am thinking about creating some benchmarks that I can understand myself. The LLM 'cheating' by finding known issues through some sort of history or online source is a path you want to protect against. Then again, you DO want them to be able to look online for people having similar issues.
This is why using multiple model families is important. Don't limit yourself by being a stan for this or that company.
Yet to be obsolete.
- For some reason choosing only a subset of issues.
- Different LLMs actually learn different things.
I suspect the former since they do this for me and it's extremely annoying sometimes
This read like a conversation you were having in your head -- unfiltered.
The lower the number the higher the priority, e.g. if production is broken someone might say "This is p -1" (higher than your highest priority).
P0 is "do this immediately", P1 is very important, P2/P3 are like "nice to haves." P100 would mean something like "we will never do this"
Deepseep-v4.1-Flash-1017 is a minor update. A major update is something like Deepseek-v5-Flash.
FWIW, GP didn't write "a bad copy" but "bad copy", referring to the marketing sentence quoted by OP, rather than the model that was just released (as I presume "a bad copy" sounds, maybe like it's called that because it's [again, presumably] distilled?). "Copy", especially in a marketing context, is a written message.
This is just my headcanon though.
An example when using a less frequent term actually reduces specificity.
Also, DS is an excellent model.
These are not mutually exclusive.
The CCP requires extensive certification for new major releases, to make sure a model doesn't do anything they don't want it to.
To get around this, Chinese labs only bump versions when they have to and usually claim it's a minor update.
Then on the other side, they're obviously trying to market to the tech crowd...
Would highly recommend it, it's IMO the only serious Western reporting about China.
as good as Gordon Chang.
- Reasoning effort = 1 is now actually usable and produces 2.5x less tokens than old weights, without intelligence lost.
- Overall 20% less tokens at each reasoning effort.
- Same intelligence and same tool-calling pattern.
More details in blog post https://sference.com/blog/deepseek-v41f-1017-benchmark
Much like Qwen 3.8 Next; which is qwen4-exp in a lot of the code/patches, there's usually a tick-tock cycle with LLMs. That said, it's hard to know for closed frontier models.
DeepSeek delivery deliberately uses confusing version numbers.
How people spend more than 200 usd monthly is beyond my understanding, are you guys so inefficient with the usage? or I am the opposite?
I tear through my $200 subscription because I often have 3-4 agents running simultaneously, exploring performance optimizations, building features, monitoring production rollouts, or investigating production problems/customer issues in parallel.
The downside is that I do spend most of my time reading the agent's output these days.
How?
This is how one of my claude code session looks like right now, one prompt from yesterday:
I created a skill to better manage agents, including a way to keep the caches valid, and it has decreased my usage considerably. I now struggle to use my 100% each week and I hit claude hard. I have a reset expiring in 5 days and I'm trying to burn down the tokens (68% with 3d 8h left) quickly so I can use my reset before it expires.
Token efficiency just means understanding the way the system works. Best person to help with that... my old friend claude.
I don't actually know the real mechanism, I came across this serendipitously.
Claude: Confirmed: 195M of the 212M cache tokens (92%) come from full re-writes after 5+ minute gaps, accounting for 77% of relative cost. Now I'll check the existing wrappers so the skill builds on them.
Can you invert things. What’s deterministic and what needs “thinking”?
Can you create a script that runs things chaining together the deterministic parts with calling out to Claude for glue that needs “thinking”.
I think the tests problem is really having an impact for me. Hadn't considered it before so thanks for flagging.
Maybe doing bogus small requests to prevent the cache from expiring?
I mean in the API you can set the cache expiration time right? But I guess claude code can't do this
Awfully new old friend.
What exactly are they doing for you that's giving you $200 of value in such a short timeframe?
- How long do you reckon it would take a human to do the task?
- What percentage of features/ feature-extensions you add would have been done at all if you didn't have agentic assistance? Is there a tension between llm productivity gains and 'because we can' feature additions?
- Are many of the tasks for throwaway v1 features, exploratory tries?
- How speced out is the work you give it, eg did this task have pages of specs, how long did the spec take to write?
- How deeply will you manually review the work and how much time will it take? Will you read all the code / review at a high level and interrogate with llm / have the llm review and self iterate?
I do now add all the major features I want, and write a task list where I add a few more minor tasks each week that just come to my mind. I need to write them down before I forget. I often ask Claude to implement several different implementations/algorithms and compare them. There are plenty of trade-offs, which usually end up in building configuration profiles, so the application can work optimally in multiple environments.
The specification is actually really large, and has grown over time as I've been learning and new ideas has come to my mind. I do not review/audit the code, it's massive would take me months, no chance! I do however use code inspection/audit tools like TSAN, ASAN and more. I will also spend time on full code reviews with the coming Fable 5.5 when a release is about ready. I do however review behavior together with Claude, and this is also where the specification grow, because this and that should be possible, but not this and that. User stories also helps.
There's no reason to blow through tokens this way, there's a 99% chance nobody uses the output (except maybe themselves).
That’s the “how” we’re wondering about.
I am not saying OP is not telling the truth. I just really want to understand!
Anyone who tells you they have a “team of subagents” and “code reviewer” agents and “project manager” agents doesn’t know what they are doing. That’s how they burn thousands of dollars in a day.
I think I’ll trust the experience of the people in the labs who have unlimited token budgets and are running experiments continuously over some anonymous rando slinging mud on the internet.
Also my own experience, which says having code reviewer agents is one billion percent useful. That comment alone completely disqualifies you as a reliable source of info.
Maybe you're not being ambitious enough with these things? They are at their most fun when you spec out sprawling architecture documents and watch 1+8 astras buzzsaw through it.
I'm only at 260B for the year, though. I'm sure someone who has used more will be along shortly to chime in
E: The other subthread talking about tests is correct. Expensive models should not waste a single second waiting on tests or validation. If you cannot assign a single cheap model to be the test bitch, then just tell them to frontload everything and clean up later as a single wave.
> Have you shipping anything?
Yes, hundreds of PRs and shipped new features to 3 different platforms (day job and 2 side-business apps/platforms I’ve been developing for many years, pre-LLM). Those new features have gone out to customers and been used.
> Do you have income from this?
Well my day job for one, and I’ve been able to more easily sell to new clients with my side business. Without the changes I’ve shipped I would have been able to land a couple of the clients I’ve signed on recently.
I don’t think OP’s message implied they are never finishing a project, maybe they edited it?
In addition to the 3 income-generating projects, I have a number of other “just for me” projects. Some are mature now and only need occasional development when I want a new feature. Some are in flux as I build them out (like my “software factory”).
At this point I’m limited by compute and tokens more than anything else.
EDIT: but thanks for a useful answer to OP's question. As a programming dabbler I also find it hard to imagine how to push much past the 5hr limit on $20USD subscription.
It’s paid for itself though, at least from my side business income.
I would be worried about your methodology when the subscription party ends. Make no mistake, one day, the party is ending and the people who are dining out on approaches that burn massive tokens are in for a rude shock.
It is like putting a jet engine on a shipping container and wondering why it needs to be constantly kept in afterburner to at least scrape on the road while smarter users put wheels on the shipping container.
There’s also zero stickiness to models and most companies now have their own internal routing utilities so devs and users can just keep the same API endpoint and move between models with a single line of code swap.
Unless something changes with the big labs and fast, they look pretty f*cked.
It is more complicated than that when the valuations and business plans are contingent on those companies AI having complete dominance at every level.
If companies only use frontier models for occasional difficult tasks, not only does that affect volume, it basically elminates stickiness and incentivizes companies to instead of using their products continuosly, find ways to move from the expensive stuff to the cheaper stuff.
You’re assuming other model creators can’t build these mega models. Evidence is they’ve simply decided it’s a fools game to do so and they’re focused on where the use cases are.
It's a bit like obsessing over patch releases of some software after a major upgrade already solved the original problem long ago.
And then when I try a smart model, like Astra medium and it solves it (I had a firmware bug in my new laptop where I couldn't charge through USB-C) on the first try (altough with a repo already having lots of information about the hardware/firmware/debugging programs/traces), I realize how much time I'm losing on the few examples that the less intelligent models are just not able to debug and solve.
Is your laptop something like framework which has open source firmware?
I(and many other people) have a similar issue with usb-c charging not working consistently. I've been meaning to try one of these new smart models to help me debug the issue.
I had to reboot my laptop a few times though until I got to this, but it was a fun experience anyways.
At this point open source isn't as much advantage as long as the firmware is not encrypted :)
I'll try handing it off to one of these new frontier models.
Like if we needed PhD intelligence for productivity tools and SaaS platforms, why weren't we hiring PhDs to build things before.
99.99% of people do not need SOTA ai.
https://www.lithosai.com/
https://www.coralbricks.ai/
Depends on your use case. But if you do software development with a harness such as oh-my-pi, your cache rates are probably somewhere above 98%. Coralbricks has free cache reads, meaning it's much cheaper than the Deepseek API rates.
Lithosai is more expensive especially in the ultra tier. It's if you want extremely snappy and fast responses, which is important e.g. for a personal assistant where every second counts.
If you generate a lot of output, you're better off with the Deepseek API rates.
Outside of major players like Amazon/Google which have compatible offerings available, I believe together.ai, fireworks.ai, and deepinfra.com are, as best as I can tell, US-based (if that matters in your situation) SOC2/HIPPA/ZDR. Each of them offer serverless model hosting with caching, which is going to be the cheapest overall. Most of them also offer private AI deployment which is more expensive but your entirely own instance. Some of them more heavily quantize their models (deepinfra) so take that into your workload considerations. I included deepinfra because they tend to have some the new models sooner than others or have models the others don’t (like mimo). IMO, together > fireworks > deepinfra.
However, you’ll have to keep in mind that for true ZDR you give up caching which increases your inference costs, so it depends on how “Zero” you need the zero to be and on what timeframe. If you just don’t want your data being trained on, normal use is fine imo. If you are working on something actually sensitive (like, because of NDA agreements and such), then they might not be the right choice and you may be looking at more expensive offerings or building a machine.
One note: you have to pay attention to the source of the inference. Many (similar to open router) offer models that are pass-throughs to a providers API, but they are pretty clearly marked. Just make sure the model is marked as serverless when evaluating new ones. This is where a proxy comes in handy so you can prevent your LLM from accessing a different models from the specific ones you’ve vetted.
What about "good governance"?
Does it have zero hallucinations? Does it reflect thoroughly on every single idea it uses, verifying its solidity?
If I'm impatient I switch to Luna for a single turn just to get it started and let DS continue.
I didn't try the last flash model because I would need to use SSD streaming (I have 128 GB), but the benches for this release are so compelling (and it using less tokens to get tasks done) it might be worth the throughput hit. I will probably give it a try when I have some downtime.
It feels very freeing to be doing useful work on a local model on my own hardware with my own coding harness. The TCO argument is starting to look compelling too.
Probably a pretty decent model for 90% of the usecases!
I've been doing a lot of hobby work with GLM 5.3 Flash and I can count the amount of times that I need a stronger model on two hands.
I have access to unlimited tokens at works and Opus is great but also often overkill if you know exactly what you need.
A very complex task tends to cost like 10$ max. It's comparable to a subscription with enormous flexibility.
It's a steal.
Since making this (obscure/hidden) change I enjoy Codex much more.
I don't think there is a reason to care about any of it, just get a few dollars on a few openrouter or similar platforms and just use the models for now, wait for cheaper models that are good enough for you to become available for your hardware.
Sure you might never see frontier performance on consumer hardware but do you really need that though? Does anyone? And if you ever do just get a 30-day sub for that work, and cancel it.
We are running Qwen 3.8 27B FP8 with 4x 5060 16gb at the office for a small development team. It is doing pretty well for implementing backend and frontend tasks, and is already useful. In 6 and 12 months from how I expect it to get even better. Some planning is still done with a stronger model, but even that is maybe not strictly necessary.
And we are likely to see many companies start building 27-32B MoE models custom built for use cases now that Rubin is going to make training costs much lower.
I expect training costs to get under 100k USD within a year for small models with another 100k maybe for RL.
I think just having all your own data from claude and stuff on your system that you can feed these models and have companies offer great base 27B models will be how it works.
MiMo 2.6 Flash is the most capable model you can currently run on 2x Sparks without resorting to a quantised version of something.
Are they as good as opus 5.5? No.
Are they about on par with opus 4.6? Yes.
The long run tasks i run seem to be about the same level of quality, though there are obvious differences in model styles, token budgets, etc....
Definitely an improvement on deepseek-v4-flash-0731: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
Looks much better.
It works when it works, but will probably be flaky AF for a few days.
Works well with Copilot:
700000 because there's no detail yet on the safe completion limit for most harnesses (OR lists 1M for both which makes no sense). COPILOT_OFFLINE enables all calls except to OR (no GH servers).As a Luna6 proponent, this has a potential as it looks slightly more intelligent and at the similar price point.
The speed and cost/intelligence ratio is just outrageous.
Lovely to see they're doing their own search though, I love how many folk are actively working on search clones at the moment.
https://slopgrid.com/deepseek-41-horses
At the beginning of the month I realized I had more tokens and more capabilities on Opencode at 8$/month via DS 4.1 flash, than I had on a 200$ account in June with the american providers.
Literally both more tokens and capabilities than Opus 4.8/GPT 5.5.
Even if you pay per token, you're still unlikely to outspend american providers.
And southern Europe isn't exactly the poorest region around.
BTW who would have thought China would be the champion of freedom and opensource in the AI arena, while US is fighting for corporate/government control.
There are different types of freedom and China's bet is that as long as they provide enough economic freedom the public will be ok with somewhat restricted social and political one.
The fact that she can't call Xi "Winnie the Pooh" on Douyin wasn't something that occurred to her, or maybe that she was aware of at all. I didn't ask. I don't like to get into these discussions when I'm in China.
Citizens of Palm Beach county cannot voice their opposition to how their tax dollars are being spent. They rightly want that money to be invested locally, instead the County uses it to invest $1B in Israeli bonds, something that people widely oppose.
They first said that it's a budget meeting and Israeli bonds are a "policy matter". Then they started arresting people for speaking out against it. Then they started arresting anyone who applauded.
"Free speech" -> I spit on American "free speech". It's the most insidious and dishonest thing. At least the CCP doesn't PRETEND to give people rights that they simply don't have.
the U.S allows "free speech" if it's inconsequential.
https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017/...
> providers have to implement which could be different than what the labs themselves use.
I'd imagine (most) providers just take implementation by vLLM/SGLang.
Right now I use each of them in their own respective coding harnesses, deepseek-harness and kimi-code, but I do wonder what they are like inside something like opencode.
OpenCode if you want a good, opinionated setup
https://arxiv.org/abs/2601.06521
DeepSeek v4.1 Flash was a beast.
It was already cheaper and more powerful than Haiku 5.5 which was released like a full month after it... by a trillion dollar american "frontier" company.
Can't wait to see what this one has in store.
I have been intrigued about Chinese models for a long time, but never tried anything except an early Qwen. My daily driver was Luna, with occasional elevation to Terra or Sol - all on 5.6 as I found the output of 6 jarringly incomprehensible.
I still had 95 USD on my OpenRouter account, so I thought I would give DeepSeek Flash 4.1 a try.
I think now I can understand the person who created that thread.
Here is the setup I settled on, after a lot of refactoring and calibration of the workflow:
I have a "plan" prompt which explains to the agent (Luna) that I want to have a discussion about an idea I have in mind. The agent should use the Socratic method to pull out all the necessary info from me using pointed questions. When the agent feels it has a complete picture, it should elevate to a higher level model (Sol), and ask its review. If Sol has complaints, Luna keeps asking me until the points raised by Sol are clarified. The review rounds with Sol continue until Sol says "ready to implement".
At this point Luna creates four files in a directory I specify:
1. PLAN.md: the implementation plan with all the details that came out from the design discussion 2. PHASES.md: implementation phases 3. DECISIONS.md: design decisions (this serves the same role as ADRs aka. architectural decision records) 4. DIARY.md: append-only log of what happened during implementation
Files 2-4 are written by the implementing agent. Luna only adds headers to explain the purpose of the files.
Once these files are there, I start up a new Pi session, switch to Deepseek 4.1 Flash and then point it to this plan folder.
And then it goes brrrrr... :-)
Here is what I implemented in the past week using this method:
1. A capture/analysis/decompilation pipeline for C64 demos: I ask the agent to start a selected demo through VICE, and say "on" or "off" when I want it to start/stop capture. The capture process uses VICE's builtin trace functionality: the trace log is piped into Clojure where it is saved into an optimized binary format (chunks of trace events). Once I have everything captured, I unleash my analysis pipeline which checks the write patterns of the executed code: what it wrote (VIC, SID, CIA, memory) and when (rasterline, cycle). Then it splits the execution trace into segments by type deduced from the write patterns (decruncher, loader, raster, music) and then decompiles each segment into both traditional ASM files and a s-exp based syntax which roundtrips back into the in-memory representation. Once I have the results of the analysis pipeline, I can tell the agent to analyze any demopart and it can explain how the effects are built down to the tiniest timing detail. As a first test, I asked it to create a clean-room implementation of Fairlight's legendary intro and two days later I had it, with everything in sexp assembly, including the music routine and its data. (The reason it took so long was that this was the first decomp and it provided a lot of feedback to the pipeline development.) Finally I had it write an assembler, linker and packager which creates a PRG from the assembled and linked artifact, then runs it through VICE. Done.
2. A DSP compiler which lets me compile sexp forms of a C-like DSP language into native DSP kernels running on the JVM, JS and WASM. Currently I have about 600 tests which verify that the behavior of the three targets matches that of a reference interpreter written in Clojure. I have a full numeric tower with i32, f32, f64, support for arrays and structs, typical control flow constructs, and a library of DSP building blocks like oscillators, filters, LFOs, delays and a chorus effect. By the time this is ready (end of the weekend?), I will be able to build synthesizers like Synth1, Surge XT or Vital in Clojure/Script, compile the DSP kernels in the browser, choosing between JS or WASM backends, driving the kernels via AudioWorklets and sequencing them from the host language.
There are two power tools at play here:
1. Deepseek Flash 4.1 2. Clojure and ClojureScript
Deepseek is a BEAST. It just goes on and delivers, phase after phase. What it needs: clear instructions - this is covered by the planning process quite well, but I still find it needs some steering from time to time (the right nudget of wisdom dropped into its thought stream at the right moment works wonders)
And Clojure... well. That article PG wrote about LISP (Beating the averages): what I witness now proves all of those claims.
The agent LOVES Clojure. Especially the REPL (not so much the parentheses).
Winning strategy: give it two tools: start_jvm and clojure_eval. Implement everything else it may need - tools to start up HTTP servers, compile ClojureScript, add dependencies, capture a C64 demo, run Playwright via spel, etc. - as lightweight Clojure namespaces which provide APIs to all these functionality. Let these namespaces be thin: the namespace and the functions therein shall have docstrings which tell the agent what the functions do, but the functions themselves shall be lightweight proxies to the real implementations in sub-namespaces. Then point the agent to these top-level API namespaces via your AGENTS.md. Bam, instant discoverability with minimal context usage. It will do EVERYTHING through clojure_eval and the round-trip time will be phenomenal, a perfect match to the raw speed of the agent.
...
Now all I need to figure out is what will I do when all my dreams become manifest in flesh.
Then I turned what Deepseek did into an upfront policy.
This seems to work quite well generally: watch the agent as it works, and think what could be provided to make its life as easy as possible
I wrote a Pi extension called "model-escalation" which lets the model request an automatic switch to a smarter model for the next turn if it thinks the problem it is struggling with is too complex or if the user explicitly asks it to do so.
With this extension in hand, I could split the work between Luna and Sol, resulting in a ~95%-5% split. I don't have to switch to Sol when review time comes, Luna does it automatically. Sol tells its remarks, then Luna gets the control back and continues the back&forth (if there are still complaints).
so AI labs can just pick which to show
https://www.reddit.com/r/DeepSeek/comments/1x84wke/deepseek_...
That's way cheaper than openai and other web search providers. I have no doubt that AI demand justifies all the compute money big tech is spending now, but I also think there are so many over valued VC funded companies that are going to crash in the next few years.
When I type deepseek on my CLI it launches Claude with my fireworks API key. Works very well and feels almost free.
I'm a communist so I'm fine, but you may not be, so be aware
[1] https://www.reddit.com/r/LocalLLaMA/comments/1x7g3zq/china_p...
Anthropic and DeepSeek (+ GLM) are definitely solving coding, though!
They're all quite different tools.
https://artificialanalysis.ai/articles/aa-3d
For me it's large files in Blender (in some cases >400MB), mostly, where Astra excels. I gave it a look, but I don't know if the benchmark encompasses that sort of thing.
.step files are simpler pieces of straightforward code, so it makes sense that Opus and Sonnet 5.5 do very well...
Besides, Fable 5.5 is reportedly releasing within the next few days, probably on Tuesday...
Here's How Distill APT Used McKinsey's Private Access To Top Anthropic Model To Help The Chinese Keep Up With The Us Top IA Labs Despite Access Restrictions
yes maybe opus 5.5 is stronger and flash is cheaper, but 6.1 strikes a good balance imo.
You can in contrast get far more done with $20 worth of deepseek api spend. No comparison.